Loss-of-function genetic variants (LoFs) often result in severe phenotypes, including autosomal dominant diseases driven by haploinsufficiency. Due to low carrier frequencies, their penetrance is generally unknown but typically variable. Here, we investigate the penetrance of >6,000 predicted LoFs (pLoFs) linked to 91 haploinsufficient diseases using a cohort of ≈24,000 carriers with linked electronic health record data. We find evidence for widespread reduced penetrance, which persisted after accounting for variant annotation artifacts, missed diagnoses, and incomplete clinical data. We thus hypothesized that many pLoFs have incomplete penetrance, which may be driven by residual allelic activity. To test this, we trained machine learning models to predict pLoF penetrance using variant-specific genomic features that may correlate with incomplete loss-of-function. The models were predictive of pLoF penetrance across a range of diseases and variant types, including those with prior clinical evidence for pathogenicity. This suggests that many pLoFs have incomplete penetrance due to residual allelic activity, complicating disease prognostication in asymptomatic carriers.

Background:Polygenic risk scores derived from coronary artery disease genome-wide association studies are associated with statin relative risk reduction. Objective:Examine the relationship between coronary artery disease polygenic risk scores that include variants below thresholds of genome-wide significance and statin primary prevention of major adverse cardiovascular events. Methods:We generated coronary artery disease polygenic risk scores for participants with no past evidence of myocardial infarction from three electronic health record-linked genetic biobanks: All of Us Research Program, Genetic Epidemiology Research on Adult Health and Aging, and the Million Veteran Program. We scored each participant using three different polygenic risk scores: two with both genome-wide and sub-genome-wide significant variants (metaGRS and PRS2022) and one with only variants meeting genome-wide significance (164SNP). We used covariate-adjusted Cox regression models to compare risk of major adverse cardiovascular events between statin users and nonusers matched on age, sex, smoking status, type 2 diabetes mellitus, and hypertension within strata defined by polygenic risk. For the primary analysis, we performed a meta-analysis across the three cohorts for the delta hazard ratio of statin effectiveness between high and low polygenic risk. Results:Across all cohorts, statin use was more strongly associated with reduced risk of major adverse cardiovascular events among participants with no myocardial infarction at index in the highest versus lowest polygenic risk score group for the PRS2022 (interaction beta 0.19, standard error 0.07, interaction P=2.3E-3) and metaGRS (interaction beta 0.14, standard error 0.07, interaction P=.02) scores. However, the association was not statistically significant (interaction beta 0.09, standard error 0.07, interaction P=.08) for the 164SNP risk score. Conclusions:We demonstrated that the association between coronary artery disease polygenic risk scores and statin relative risk reduction can by enhanced with the inclusion of sub-genome-wide variants, paving the way for more research to establish clinical utility.

BACKGROUND AND OBJECTIVES:Previous research of associations between statins and Alzheimer disease and Alzheimer disease-related dementias (AD/ADRDs) has been limited by short follow-up, small samples, and confounding. We aimed to estimate the association between the 1st statin prescription and incident AD/ADRD among members of a large population-based cohort of older adults. METHODS:We used a cohort study design emulating a target trial using data from Kaiser Permanente Northern California (KPNC), an integrated health care delivery system. Participants were born before 1951 and KPNC members for 4+ years during 1997-2010. Embedded subsamples included sociodemographic and genetic data. Statin initiators were matched at first prescription ("baseline") with up to 5 "noninitiators" based on age and low-density lipoprotein cholesterol (LDL-C). Participants with extreme propensity scores were excluded. The outcome was time to incident AD/ADRD diagnosis, censoring, or the administrative end of study (December 31, 2020). Cox proportional hazard models were used to estimate hazard ratios for statin initiation on AD/ADRD incidence. Follow-up time was divided at the first year of follow-up to account for increased AD/ADRD detection in the first year due to increased interaction with the health care system after a statin prescription. RESULTS:Among eligible participants (n = 705,061), 264,294 individuals (37.5% of eligible participants) initiated any statin during 2001-2010 ("initiators"), of whom 249,613 (94.4%) were matched with 255,937 unique noninitiators to create the analytic sample (322,358 unique participants; mean age at baseline = 67.4 years; 55.1% female). The average follow-up was 11.8 years. In the first year after initiating statins, AD/ADRD diagnoses were elevated by 46% (hazard ratio [HR] = 1.46, 95% CI 1.42-1.53) compared with noninitiators. After 1 year, statin initiators experienced no difference in AD/ADRD incidence (full sample: HR = 1.00, 95% CI 0.99-1.01; subsample with survey covariates: HR = 1.01, 95% CI 0.98-1.06; subsample with survey and genetic covariates: HR = 0.97, 95% CI 0.91-1.07). Adjustment for sociodemographic covariates and apolipoprotein E e4 allele count did not materially change the findings. DISCUSSION:In this large emulated target trial, statin initiation was inconsistent with more than a 3% increase or decrease in the hazard of AD/ADRD after the first year of follow-up. This intent-to-treat analysis does not directly quantify effects of long-term exposure to statins. Associations in the first year likely reflect increased medical observation immediately after statin initiation. CLASSIFICATION OF EVIDENCE:This emulated trial provides Class II evidence that statin initiation is not associated with AD/ADRD or AD incidence after the first year of follow-up.

Background and ObjectivesPrevious research of associations between statins and Alzheimer disease and Alzheimer disease-related dementias (AD/ADRDs) has been limited by short follow-up, small samples, and confounding. We aimed to estimate the association between the 1st statin prescription and incident AD/ADRD among members of a large population-based cohort of older adults.MethodsWe used a cohort study design emulating a target trial using data from Kaiser Permanente Northern California (KPNC), an integrated health care delivery system. Participants were born before 1951 and KPNC members for 4+ years during 1997-2010. Embedded subsamples included sociodemographic and genetic data. Statin initiators were matched at first prescription ("baseline") with up to 5 "noninitiators" based on age and low-density lipoprotein cholesterol (LDL-C). Participants with extreme propensity scores were excluded. The outcome was time to incident AD/ADRD diagnosis, censoring, or the administrative end of study (December 31, 2020). Cox proportional hazard models were used to estimate hazard ratios for statin initiation on AD/ADRD incidence. Follow-up time was divided at the first year of follow-up to account for increased AD/ADRD detection in the first year due to increased interaction with the health care system after a statin prescription.ResultsAmong eligible participants (n = 705,061), 264,294 individuals (37.5% of eligible participants) initiated any statin during 2001-2010 ("initiators"), of whom 249,613 (94.4%) were matched with 255,937 unique noninitiators to create the analytic sample (322,358 unique participants; mean age at baseline = 67.4 years; 55.1% female). The average follow-up was 11.8 years. In the first year after initiating statins, AD/ADRD diagnoses were elevated by 46% (hazard ratio [HR] = 1.46, 95% CI 1.42-1.53) compared with noninitiators. After 1 year, statin initiators experienced no difference in AD/ADRD incidence (full sample: HR = 1.00, 95% CI 0.99-1.01; subsample with survey covariates: HR = 1.01, 95% CI 0.98-1.06; subsample with survey and genetic covariates: HR = 0.97, 95% CI 0.91-1.07). Adjustment for sociodemographic covariates and apolipoprotein E e4 allele count did not materially change the findings.DiscussionIn this large emulated target trial, statin initiation was inconsistent with more than a 3% increase or decrease in the hazard of AD/ADRD after the first year of follow-up. This intent-to-treat analysis does not directly quantify effects of long-term exposure to statins. Associations in the first year likely reflect increased medical observation immediately after statin initiation.Classification of EvidenceThis emulated trial provides Class II evidence that statin initiation is not associated with AD/ADRD or AD incidence after the first year of follow-up.

Loss-of-function variants (LoFs) can result in severe clinical phenotypes, including both autosomal-recessive and -dominant Mendelian diseases. Except for a handful of unusually common variants, however, their lifetime risk for disease expression is unknown. This is particularly true for LoFs in genes linked to autosomal-dominant diseases driven by haploinsufficiency, which represent some of the most common monogenic disorders. Here, we investigate the disease-expression rates for >6,000 predicted LoFs (pLoFs) linked to 91 haploinsufficient diseases using the electronic health records (EHRs) of ∼24,000 pLoF heterozygotes isolated from two population-scale biobanks (the UK Biobank and the All of Us Research Program). Consistent with prior analyses, most pLoF heterozygotes displayed no evidence for disease expression, a phenomenon that persisted after accounting for variant annotation artifacts, missed diagnoses, and incomplete clinical data. While it is infeasible to completely remove all the artifacts and biases from EHR data, we hypothesized that many of these pLoFs have intrinsically low or even no penetrance, which may be driven by residual allelic activity. To test this, we trained machine-learning models to predict disease-expression risk for pLoFs using only their genomic features. In validation experiments, the models were predictive of pLoF disease-expression rates across a range of diseases and variants, including those previously annotated as pathogenic by diagnostic-testing laboratories. This suggests that many pLoFs have intrinsically incomplete or even no penetrance (i.e., are benign) due to residual allelic activity, complicating prognostication in asymptomatic individuals.

Genetic substudies of randomized controlled trials demonstrate that high coronary heart disease (CHD) polygenic risk score modifies statin CHD relative risk reduction; it is unknown if the association extends to statin users undergoing routine care. We sought to determine how statin effectiveness is modified by CHD polygenic risk score in a real‐world cohort of participants without previous myocardial infarction. We determined CHD polygenic risk scores in participants of the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. Covariate‐adjusted Cox regression models were used to compare the risk of cardiovascular outcomes between statin users and matched nonusers. Statin effectiveness on incident myocardial infarction showed no gradient with increasing 10‐year Pooled Cohort Equations atherosclerotic cardiovascular disease (ASCVD) risk across low, borderline, intermediate, and high ASCVD risk score groups. In contrast, statin effectiveness by polygenic risk was largest in the high polygenic risk score group (hazard ratio (HR) 0.41, 95% confidence interval (CI), 0.31–0.53; P = 1.5E‐11), intermediate in the intermediate polygenic risk score group (HR 0.56, 95% CI, 0.47–0.66; P = 8.4E‐12), and smallest in the low polygenic risk score group (HR 0.67, 95% CI, 0.47–0.97; P = 0.03; P for high vs. low = 0.01). ASCVD risk and statin low‐density lipoprotein cholesterol (LDL‐C) lowering did not differ across polygenic risk score groups. In patients undergoing routine care, CHD polygenic risk modified statin relative risk reduction of incident myocardial infarction independent of LDL‐C lowering. Our findings extend prior work by identifying a subset (i.e., self‐identified White individuals with low CHD polygenic risk scores) with attenuated clinical benefit from statins.

Here we report results from the Bipolar Exome (BipEx) collaboration analysis of whole exome sequencing of 13,933 individuals diagnosed with bipolar disorder (BD), matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in BD patients among genes under strong evolutionary constraint, a signal evident in both major BD subtypes, bipolar 1 disorder (BD1) and bipolar 2 disorder (BD2). We also find an excess of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 SCZ cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from GWAS of BD, however, are not significantly enriched for ultra-rare PTVs. Combining BD gene-level results with SCHEMA, AKAP11 emerges as a definitive risk gene (ultra-rare PTVs seen in 33 cases and 13 controls, OR = 7.06, P = 2.83 x 10-9). At the protein level, AKAP-11 is known to interact with GSK3B, the hypothesized mechanism of action for lithium, one of the few treatments for BD. Overall, our results lend further support to the polygenic basis of BD and demonstrate a role for rare coding variation as a significant risk factor in BD onset.

Bipolar disorder (BD) is a serious mental illness with substantial common variant heritability. However, the role of rare coding variation in BD is not well established. We examined the protein-coding (exonic) sequences of 3,987 unrelated individuals with BD and 5,322 controls of predominantly European ancestry across four cohorts from the Bipolar Sequencing Consortium (BSC). We assessed the burden of rare, protein-altering, single nucleotide variants classified as pathogenic or likely pathogenic (P-LP) both exome-wide and within several groups of genes with phenotypic or biologic plausibility in BD. While we observed an increased burden of rare coding P-LP variants within 165 genes identified as BD GWAS regions in 3,987 BD cases (meta-analysis OR = 1.9, 95% CI = 1.3–2.8, one-sided p = 6.0 × 10 −4 ), this enrichment did not replicate in an additional 9,929 BD cases and 14,018 controls (OR = 0.9, one-side p = 0.70). Although BD shares common variant heritability with schizophrenia, in the BSC sample we did not observe a significant enrichment of P-LP variants in SCZ GWAS genes, in two classes of neuronal synaptic genes (RBFOX2 and FMRP) associated with SCZ or in loss-of-function intolerant genes. In this study, the largest analysis of exonic variation in BD, individuals with BD do not carry a replicable enrichment of rare P-LP variants across the exome or in any of several groups of genes with biologic plausibility. Moreover, despite a strong shared susceptibility between BD and SCZ through common genetic variation, we do not observe an association between BD risk and rare P-LP coding variants in genes known to modulate risk for SCZ.

The association between the c.521T>C variant allele in SLCO1B1 (reference single nucleotide polymorphism (rs)4149056) and simvastatin‐induced myotoxicity was discovered over a decade ago; however, whether this relationship represents a class effect is still not fully known. The aim of this study was to investigate the relationship between rs4149056 genotype and statin‐induced myotoxicity in patients taking atorvastatin and lovastatin. Study participants were from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. A total of 233 statin‐induced myopathy + rhabdomyolysis cases met the criteria for inclusion and were matched to 2,342 controls. To validate the drug response phenotype, we replicated the previously established association between rs4149056 genotype and simvastatin‐induced myotoxicity. In particular, compared with homozygous T allele carriers, there was a significantly increased risk of simvastatin‐induced myopathy + rhabdomyolysis in homozygous carriers of the C allele (CC vs. TT, odds ratio [OR] 4.62, 95% confidence interval [CI] 1.58–11.90, P = 0.003). For lovastatin users, homozygous carriers of the C allele were also at increased risk of statin‐induced myopathy + rhabdomyolysis (CC vs. TT, OR 4.49, 95% CI 1.68–10.80, P = 0.001). In atorvastatin users, homozygous carriers of the C allele were twice as likely to experience statin‐induced myopathy, though this association did not achieve statistical significance (CC vs. TT, OR 2.00, 95% CI 0.44–6.59, P = 0.30). In summary, our findings suggest that the association of rs4149056 with simvastatin‐related myotoxicity may also extend to lovastatin. More data is needed to determine the extent of the association in atorvastatin users. Altogether, these data expand the evidence base for informing guidelines of pharmacogenetic‐based statin prescribing practices.

We describe an 11-year old boy with severe global developmental delays, failure to thrive and growth retardation, refractory seizures with recurrent status epilepticus, hypogammaglobulinemia, hypergonadotropic hypogonadism, and duodenal strictures. He had facial and skin findings compatible with trichothiodystrophy, including sparse and brittle hair, thin eyebrows, and dry skin. Exome sequencing showed a hemizygous, truncating variant in RNF113A, c.903_910delGCAGACCA, predicting p.(Gln302fs*12), that was inherited from his mother. Although his clinical features overlap closely with features described in the two previously reported male first cousins with RNF113A loss of function mutations, the duodenal strictures seen in this patient have not been reported. Interestingly, the patient's mother had short stature and 100% skewed X-inactivation as seen in other obligate female carriers. A second male with developmental delays, microcephaly, seizures, ambiguous genitalia, and facial anomalies that included sparse and brittle hair, thin eyebrows and dry skin was recently reported to have c.897_898delTG, predicting p.(Cys299*) in RNF113A and we provide additional clinical details for this patient. This report further supports deleterious variants in RNF113A as a cause of a novel trichothiodystrophy syndrome.

For those of you who aren’t familiar, here is a picture of a LaSalle (Figure 1). Is that not a gorgeous car? I definitely covet one of those!Figure 1A La Salle AutomobileShow full caption“La Salle Series 39-5067 Convertible Coupé 1939” (https://commons.wikimedia.org/wiki/File:La_Salle_Series_39-5067_Convertible_Coupe_1939.jpg); photo taken by Lars-Göran Lindgren Sweden and licensed under the CC-BY-SA 3.0 license (https://creativecommons.org/licenses/by-sa/3.0/deed.en).View Large Image Figure ViewerDownload Hi-res image Download (PPT) “La Salle Series 39-5067 Convertible Coupé 1939” (https://commons.wikimedia.org/wiki/File:La_Salle_Series_39-5067_Convertible_Coupe_1939.jpg); photo taken by Lars-Göran Lindgren Sweden and licensed under the CC-BY-SA 3.0 license (https://creativecommons.org/licenses/by-sa/3.0/deed.en). I am going to start off by thanking a bunch of people—particularly the staff, whose pictures are up here. There are many more on the staff; these are just some that I picked out. Of course, everyone knows Pauline, who is really in charge of this meeting. And as I told her, people tell me, “This is your meeting!” Well, not exactly. And it’s been an incredible honor to work with Joe and the rest of the staff. Their pictures are here—so if you see them during the meeting, please go up and thank them. It is an enormous amount of work to put forward this meeting. Another person who has done an enormous amount of work is our fearless and tireless program chair, Chris Gunter. We owe her, as well as the entire program committee, a big debt of gratitude; as you can imagine, reviewing 3,000+ abstracts is a big chore, and programming it all and having it all make sense are really difficult. So, as you go through the meeting this week, if you see Chris or people on the program committee, please thank them; I think they have done, as you will see during the week, a fantastic job with the meeting. I want to thank everyone who voted for me. Some of you have complained before that we only have one candidate for president listed on the ballot. But it turns out that my presidential race was more competitive than you might think. That is because we allow write-in candidates. Technically, we don’t usually show election voting results, but in this case we are going to make an exception. Here are the actual results from my election:Neil Risch: 546Donald Duck: 221Ben Tennyson: 195Coraline: 112 And, as you can see, it was very close. But fortunately I was able to defeat Donald, Ben, and Carlie. So, it appears that at least for the ASHG presidential election, prior experience is not disqualifying. In seriousness, I really do want to thank the society for this tremendous honor and privilege. It has been an exciting year for me. I still have a few more months to go, but it’s just been wonderful, and I recommend it to any of you who ever thought about doing a job like this—it’s an exciting and wonderful thing to do. I want to welcome everyone to Baltimore also. This is the fifth time we’ve met in Baltimore, which actually ties for the most visited venue. It ties with my home town, San Francisco, and San Diego. But, sadly, at least for the near future, this is going to be the last time, and that’s because we have just outgrown it. The venue is not big enough; the society has grown so much over the last several decades that we now have fewer venues available. You’ve probably seen this before, but here is a plot showing the growth of our meeting over the past 35 years. There’s been a 7-fold increase (Figure 2). And what I am displaying here (Figure 3), if you look at the blue bars, is the diversity of meeting venues for the first three decades of the society; the red represents the last three decades. You can see dramatically greater diversity in the venues in the first three decades—there are many places we visited one time—in the early history of the society. But that is not happening any more—we are much more restricted in the locations we can go. There are pluses and minuses to being large, and one of the minuses is that we don’t have as much diversity in the locations that we visit anymore.Figure 3Diversity of ASHG Meeting Venues between the First 30 years and the Last 30 YearsView Large Image Figure ViewerDownload Hi-res image Download (PPT) I think as many past presidents have done, I looked at the past presidential addresses to try to get some guidance about what to talk about. So, I thought, let’s hear what others have said. Here is a list of some things that others have noted:•That the speech is a daunting task that keeps you up at night•Requests that members be engaged•Trends in membership size•Prior content of presidential addresses•That we are living in rapidly changing times (this has been said many times)•That everything has already been said•That this talk will be long forgotten … It started getting frustrating because everything I had thought of to say had already been said. In fact, if you look at the second-to-last comment on this list, that had already been said. So I couldn’t even say that everything had already been said. So where did that leave me? I think it was Jeff Murray who said (and I’m paraphrasing), “This talk will be long forgotten.” So I said to myself, is that really true? I decided to test this out and see. I did a lot of work here—you will think it was totally ridiculous, I’m sure. I looked at the number of citations of all the prior presidential addresses (Figure 4). The majority of presidential addresses have been cited fewer than 20 times. Only a few have been cited more than that—in fact, six have been cited more than 50 times. One of them has been cited 723 times. I know this is a big room here, but does anyone want to shout out if they know whose that was? The most cited one was the first one (Figure 5). This is a very famous paper, “Our Load of Mutations” by Herman Muller.1Muller H.J. Our load of mutations.Am. J. Hum. Genet. 1950; 2: 111-176PubMed Google ScholarFigure 5The Most Often Cited Presidential Address Is the First OneView Large Image Figure ViewerDownload Hi-res image Download (PPT) Ah, Aravinda got the right answer. He would be the one to know. He is a past president and probably did the same analysis; it wouldn’t surprise me in the least. This famous paper is still current, and people are still citing it today. I then looked back at the distributions of citations without that one, and it turns out that there is a very negative regression line (Figure 6) toward few citations for the more recent ones. In fact, I noticed that for the past 10 years, the median number of citations for presidential addresses has been two, and then I discovered that those were actually self-citations! This was great news for me because the pressure is off! So, I decided to “go for broke.” Here goes—fasten your seat belts! As president, I took the job seriously. At least I tried to. You can judge whether I did or not! I read the bylaws. Now, I don’t know how many of you have actually read the bylaws. I did actually read the bylaws, more than once. And this one about the committees struck me:ARTICLE VIII – COMMITTEES Committee members, except those serving by virtue of holding other office, shall be appointed by the President and may be removed by a majority vote of the Board of Directors. The President’s appointments shall, to the extent possible, reflect the diversity of the Society’s membership. But it doesn’t say how diversity is to be defined. So I didn’t know what I was supposed to do here. Is it by professional orientation, by advanced degree, by gender, by race or ethnicity, or by other socio-demographic factors? What I decided to do was an analysis of the diversity of the society throughout its history because I thought that could give me guidance in terms of these appointments. Here are the results. There have been 200 members who have been elected to the board of directors. I found them all by looking at the back of The Journal, since they are all named there, and then I went to Wikipedia and Google and discovered them and found out as much information about them as I could (Table S1). And one of the things I found out about every one of those 200 board members was their degree. Here are the numbers (Figure 7). It turns out that there is a pretty even split between the PhDs and the MDs and a decent number of MD-PhDs. Probably many of you don’t realize we’ve had a dentist, five people with master’s degrees, and one person with a bachelor’s degree serve on the board of directors, and we actually had one person who didn’t have a college degree. That was in the older days, which I found very interesting. The other thing I wanted to do was to see whether there has been a trend toward a change in the structure of the board and the president in terms of their degrees. I did not anticipate the results—it was a big surprise. There has been a dramatic change (Figure 8). At the beginning, in the early years of the society, primarily PhDs were in the leadership, but come the 1970s and 1980s, there was a complete reversal: the MDs were of prominence in the society. However, since 1990 we have been seeing a reversal again, and we see now, true of the board and the president, an ascendance of PhDs. I did not do an analysis to try to figure out what was underlying this trend, but I am guessing that over the past few decades we have been driven by technology, because this is the era of the genome; the genome sequence has understandably brought a lot of people into the field. It is a very exciting time. We will see whether there is going to be a shift again because there is often a lag time between the discoveries related to the human genome and when they are translated into clinical practice. You saw that another category I had on the list before is gender, so I wanted to see the female proportion of those who have served as various ASHG officers (Figure 9). The highest percent (about 28%) is for the board of directors, followed by the secretary (23%) and the president (about 16%). Treasurer, interestingly, has been about 12%, and the lowest, actually, has been for journal editor. There have been 14 editors in the history of the society, and we’ve had one woman. I think everyone knows who that is: Cynthia Morton, who has served the society in many roles, including that one. I also wanted to look at the trend over time to see whether there have been changes; it has been very dramatic (Figure 10). The female proportion of those serving on the board of directors and as president has increased, particularly for the board of directors. For the past 15 years, the board of directors has been over 50% female. We’re not quite there yet with the president, which is more in the range of 25%, so maybe we need to do a little more work there. In other surveys we have looked at, the female proportion of the general membership is actually more than 50%. So overall, this is a good trend. Here is some other demography. I wanted to also look at the race and ethnicity of the board members and presidents (Table 1). It turns out that 97.5% of board members have been white, and it’s almost the same for the presidents. On the board, we have had four Asians and one Latino and no African Americans; for presidents, it has been pretty much the same—we have had three Asians, and all the rest have been white.Table 1Demography of Elected ASHG Board of Director Members and PresidentsGroupNumber (%)Board of Director MembersPresidentsAsian4 (2.0%)3 (4.5%)Black0 (0.0%)0 (0.0%)Latino1 (0.5%)0 (0.0%)White194 (97.5%)64 (95.5%)LGBT1 + ? (0.5% + ?)1 + ? (1.5 + ?) Open table in a new tab One category we don’t routinely ask about—and wasn’t particularly easy to discover in Wikipedia either—is individuals from the LGBT community. So that one was a little harder for me to figure out. But, I can assure you that at least one individual from the LGBT community has served both on the board of directors and as president. Do I hear those tweets going? I hear a lot of tweets. OK. I also want to take this opportunity to congratulate our newly elected officers: Nancy Cox, Nico Katsanis, Charles Rotimi, and Sarah Tishkoff. I don’t think I need to point out to you that this is the first time in 66 years of this society that an individual of African descent has served on our board of directors. And I think it is about time! I was also curious about the fact that we see more women in the society and in leadership roles. I was wondering whether this trend mimics what has been going on in society more broadly. It turns out that yes, it does (Figure 11). There’s actually been a dramatic increase over the past five or six decades in terms of the number of individuals who have achieved college educations—bachelor’s degrees, master’s degrees, and doctoral degrees. But it’s been more dramatic for women. If we look at the sex ratio (Figure 12), the increase is also very dramatic—for bachelor’s and master’s degrees, back in 1950, it was three women for every ten men. Today, it is the opposite—the female-to-male ratio is 1.3 to 1.4. For the doctoral degrees, you can see the same thing. In the first three decades, it was flat, but the past four decades have seen a dramatic increase in doctoral degrees among women. In fact, the ratio is now above 1; there are more females than males with doctoral degrees.Figure 12Female-to-Male Sex Ratio of Advanced Degrees over TimeShow full captionDerived from data in Figure 11.View Large Image Figure ViewerDownload Hi-res image Download (PPT) Derived from data in Figure 11. I would just like to make a point about this, which is going to be relevant before long. Prior to the 20th century, it was commonly believed that men were intellectually superior to women. It was argued that this was because women were not capable of the same level of rational thinking that men were and hence were less suited to science than to household work. Furthermore, early brain studies concluded that women were intellectually inferior because they had smaller and lighter brains. Fortunately, we are past all that—all that has changed. As I showed you, women now exceed men in educational achievement across the board. So that is definitely the good news. Now here is the bad news: “Is an Educated Wife Hazardous to Your Health”? I don’t know how many of you guys out there have seen this article,3Suarez L. Barrett-Connor E. Is an educated wife hazardous to your health?.Am. J. Epidemiol. 1984; 119: 244-249Crossref PubMed Scopus (33) Google Scholar but it turns out that a wife who is more educated than you are can be hazardous to your health. In fact, the risk of cardiovascular disease is significantly increased if your wife is smarter than you. So, good luck, guys! While we are on the topic of education—remember I said I was going for broke here—let’s talk about the genetics of educational attainment. In the “old days” (this is part of my theme), education, income, and socio-economic status were considered social covariates in genetic studies. Now it appears that they have become the direct object of genetic analysis. Recent studies have argued that educational attainment is just a surrogate for cognitive ability or IQ. In genome-wide association studies (GWASs), SNPs have been associated with educational attainment. Triggered by this, an editorial in Nature4Editorial. (2013). Dangerous work: Behavioural geneticists must tread carefully to prevent their research being misinterpreted. Nature 502, 5–6.Google Scholar referred to this type of study as “Dangerous Work” and said that behavioral genetics must tread carefully here to prevent misinterpretation. Furthermore, the editorial made the following comment later on:Be accurate. Researchers should design studies on the basis of sound scientific reasoning. For instance, in light of increasing evidence that race is biologically meaningless, research into genetic traits that underlie differences in intelligence between races … will produce little. Really? If that is the case, why are we doing genetic-ancestry adjustments in all of our GWASs? Why are we doing admixture-mapping analyses? If I were to do a GWAS of race and ethnicity, what do you think that would produce? To me, there is a disconnect here. Here is the problem. The following paper was pretty much inevitable: “A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation.”5Piffer D. A review of intelligence GWAS hits: their relationship to country IQ and the issue of spatial autocorrelation.Intelligence. 2015; 53: 43-50Crossref Scopus (36) Google Scholar I don’t know whether you have seen this (it came out a few weeks ago), but the author did an analysis looking at the relationship between country IQ and SNP scores based on those GWASs. The paper included a scatter plot of national IQs and a Polygenic IQ SNP Score (“PISS”). And sure enough, what the author showed is that there is a strong correlation: African populations have the lowest SNP scores and the lowest country IQs, the folks in the middle are Latinos, up to the right are Europeans, and in the upper right corner are East Asians. The author then concluded,It is thus likely that the vast majority of mutations affecting intelligence were already present in the ancestral African population and as humans settled in different parts of the world, these polymorphisms were subject to directional selection pressure, which produced an overall increase in human intelligence at different rates in different geographical areas. As I said, you could almost see this coming. So, I thought, let’s look more carefully at these data. I examined SNP data in dbSNP for the major HapMap populations and calculated a mean PISS for the same SNPs. Just as the previous author had found, the mean PISS was 3.7 for Europeans, 4.4 for Chinese, 4.0 for Japanese, and 2.3 for Yorubans. However, are you aware that there are two more individuals with genotype data in dbSNP? Yes, James Watson and Craig Venter. Their scores are provided together with the HapMap populations in Figure 13. As you can see, James Watson has a PISS that is slightly lower than that for the average European, and Craig Venter has a PISS equal to the average for Yorubans. Apparently, a below-average PISS is still adequate to obtain a Nobel Prize and National Medal of Science. Or perhaps the PISS just has limited predictive value. So what is this all about? Once again, 2 weeks ago, Science magazine published an editorial6Mervis J. BEHIND THE NUMBERS. GOP legislators choke on ozone standards.Science. 2015; 349: 1268Crossref PubMed Scopus (1) Google Scholar discussing the ecological correlation between asthma prevalence and ozone levels because ozone levels have dropped but asthma prevalence has gone up, so therefore one might conclude that we don’t have to regulate ozone (Figure 14). The author needed to point out once again that correlation does not equal causation. Here is another, more relevant example. Suppose I did a genetic study 50 years ago of educational attainment. What would I have found? I would have found a very strong genetic component—the presence of a Y chromosome. Doing the same genetic study today, I would find exactly the same thing, except that the effect would be in exactly the opposite direction. So what is the problem here? The flaw in this conclusion is to think that what matters is the biology of the individual rather than the social context in which he or she lives. Is educational attainment really a proxy for IQ or, more likely, for household income? Here, I am showing (Figure 15) the probability that a child will get a college education as a function of the income level of the family. The data are for the years 2003–2005 from the US Census. The line represents the probability that a child will receive a bachelor’s degree by age 24 for each interval of household income in relation to the highest income category (>$150,000). You see that the difference is dramatic—there is an 8-fold lower probability for the bottom quintile. This difference has actually been increasing over the last four decades.7University of Pennsylvania Alliance for Higher Education and DemocracyEquity Indicator 5: How Does Bachelor’s Degree Attainment Vary by Family Income?.in: Indicators of Higher Education Equity in the United States: 45 Year Trend Report, 2015 Revised Edition. Pell Institute, 2015: 30-33http://www.pellinstitute.org/downloads/publications-Indicators_of_Higher_Education_Equity_in_the_US_45_Year_Trend_Report.pdfGoogle Scholar In response to this, Sabrina Tavernise of The New York Times wrote an editorial entitled “Education Gap Grows between Rich and Poor, Studies Say”8Tavernise, S. (2012). Education Gap Grows between Rich and Poor, Studies Say. The New York Times, February 10, 2012. A1. http://www.nytimes.com/2012/02/10/education/education-gap-grows-between-rich-and-poor-studies-show.html?_r=0.Google Scholar:Researchers are finding that while the achievement gap between white and black students has narrowed significantly over the past few decades, the gap between rich and poor students has grown substantially during the same period. Now I am going to talk about some other trends I see going on. The field has really been moving away from family-based studies to case-control and cohort studies for gene discovery and characterization—and maybe I am partly responsible for that. But it makes sense, because in the era of genomics, you can assay the genome and you can assay the genome in everyone, so it’s understandable why that has happened. As we are moving toward whole-exome and whole-genome sequencing, we are moving from genetics to genomics; no longer does positional cloning have the same degree of prominence in our work. But it has also led to a shift in causal inference, because historically causal inference was based on segregation of variants in families and based on statistics. Now, it’s based not on statistics at all but on subjective judgments of variants. So, ironically, to me, in the old days you would look at families to assess inheritance and transmission, but now families are being used for proving that a variant is not inherited because de novo mutation is one of the criteria required for something to be considered a functional variant. Also, there have been major shifts in the demography of families because mating patterns have changed—there’s more inter-racial mating, and this obviously has an impact on association studies, but other things too. This is a paper from my post doc Yambazi Banda, who did an analysis of our Kaiser GERA cohort9Banda Y. Kvale M.N. Hoffmann T.J. Hesselson S.E. Ranatunga D. Tang H. Sabatti C. Croen L.A. Dispensa B.P. Henderson M. et al.Characterizing Race/Ethnicity and Genetic Ancestry for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort.Genetics. 2015; 200: 1285-1295Crossref PubMed Scopus (192) Google Scholar (this is work that we do at Kaiser; Cathy Schaefer here is my colleague in that resource). In the 100,000 subjects who we genotyped, he looked at the population structure and its relationship with race and ethnicity. This is basically what we found: approximately 12%–17% of the cohort had ancestry from more than one continent. But more interesting, maybe, is the fact that among various combinations of racial and ethnic categories, we observed 50 different combinations. Whereas 6% of the cohort overall endorsed more than one category, that number is likely to grow as mating patterns continue to evolve. Thus, although myriad genetic markers can provide accurate estimates of individuals’ genetic ancestry, characterizing the social aspects of race and ethnicity might be more challenging. This leads me to one of my final topics, which is genetics and social identities. When it comes to our social identities, the concept of “choice” appears to loom large. I’m so glad I actually got to include a line from an episode from All in the Family. This comes from a classic episode, probably the most widely seen episode. Sammy Davis, Jr. comes to visit Archie Bunker, and they’re sitting there chatting. At one point, Archie turns to Sammy and says, “Sammy, [there’s] something I always wanted to ask you … You being colored, well, I know you had no choice in that. But whatever made you turn Jew?” So what does this come down to? It comes down to the public’s perception of what is a choice. But then I ask, why does it matter? Why and when would it matter whether something is a choice or not? This struck me also—the public’s perception of the degree to which gender or sex is biological and genetic versus its perception about whether race and ethnicity are genetic or not. The way I am looking at this is their response to individuals who are transgender or transracial. Can you change your gender socially? Can you change your race socially? I was struck by the great difference in the public reactions to Caitlyn Jenner (transgender) and Rachel Dolezal (transracial)—there was a much more positive reaction to Caitlyn Jenner than to Rachel Dolezal (Figure 16). So, is this saying something about people’s feelings about being transgender versus being transracial? What about being “trans-religion”? You might think that is easily malleable because people can convert and change religions. But maybe not. I don’t know whether you saw this—this is the result of a CNN poll10Agiesta, J. (2015). Misperceptions persist about Obama’s faith, but aren’t so widespread. CNN Politics, September 14, 2015. http://edition.cnn.com/2015/09/13/politics/barack-obama-religion-christian-misperceptions/.Google Scholar that asked people about President Obama’s religion: 39% said he was Protestant, 4% said Catholic, 29% said Muslim, 2% said Mormon, 1% said Jewish, 11% said “not religious,” and 14% said “don’t know.” Among republicans, the percentage saying Muslim exceeded that saying Protestant. But this raised a question in my mind—does a high percentage of the public believe that Obama is Muslim because his biological father was Muslim or because his adoptive father was Muslim? Even though he has identified for decades as a Christian, can you not have a religious identity that is different from that of a parent? Now another big question: why is it that homosexuality is genetic but race is not? Have the genetic studies of sexual orientation really been so conclusive? Then I’m going to ask another question: where are the genetic studies that reveal the brain structures involved in homophobia, which is also presumably familial and heritable? Now I am going to quote from Samantha Allen, who wrote the following in The Daily Beast in an article titled “The Problematic Hunt for a ‘Gay Gene’”11Allen, S. (2014). The Problematic Hunt for a ‘Gay Gene.’ The Daily Beast, November 20, 2014. http://www.thedailybeast.com/articles/2014/11/20/the-problematic-hunt-for-a-gay-gene.html.Google Scholar:The popular media, once so easily convinced by LeVay that homosexuality resulted from brain size and by Hamer that homosexuality was genetic, promptly changed its tune that homosexuality is now epigenetic. Hooray? If it’s hard to get excited about these studies, it’s because, at this point, biological explanations for homosexuality are like iPhones—a new one comes out every year …In terms of promoting LGBT equality, it doesn’t seem to matter as much whether people believe that gay people were “born that way” as it does that they simply know someone who is currently gay, no matter how they were born. Friendship is the trump card in the movement for equality, not etiology. Now, do all gay men and women want to get married? Maybe not. I don’t know how many of you have seen this cartoon from The New Yorker (Figure 17)—in case you can’t read it, it says “Gays and lesbians getting married—haven’t they suffered enough?” So, if many gay men and women do not choose to get married, what is this really about? From the recent Supreme Court ruling,12Supreme Court of the United States (2015). Obergefell et al. v. Hodges, Director, Ohio Department of Health, et al. No. 14-556. Certiorari to the United States Court of Appeals for the Sixth Circuit, June 26, 2015. http://www.supremecourt.gov/opinions/14pdf/14-556_3204.pdf.Google Scholar I quote,The marriage laws at issue are in essence unequal: Same-sex couples are denied benefits afforded opposite-sex couples and are barred from exercising a fundamental right. Especially against a long history of disapproval of their relationships, this denial works a grave and continuing harm, serving to disrespect and subordinate gays and lesbians. Pp. 18–22. Now, I live in San Francisco, and I do watch TV occasionally, and right after the ruling they did interview folks on TV, and I was struck by some of the comments. In particular, one woman said, “I can be free; I can be me.” Then they interviewed another man, who said, “For the first time in my life, I feel like a human being.” I repeat, “For the first time in my life, I feel like a human being.” Now, I think those four dissenting Supreme Court Justices should hear that, over and over and over again, until it finally sinks in. Isn’t that what this is all really about—that no one should have to go through life feeling that he or she is something less than human? And for us as geneticists, what is most important is that genetics and geneticists should in no way contribute to those kinds of negative feelings on the part of anyone, no matter who they are or what their life choices are. Now, back to families. What is it that is transmitted in families? There are many things, such as ethnicity or sexual orientation (whether due to genetics or otherwise), that parents might not be able to influence about their child. However, parents do have a direct influence on how their child feels about him- or herself, and that is what really matters. I also wanted to say a few words about mentorship. I once had an African American student say to me that he had no role models. This is probably one of the most difficult things I have ever heard from a student. But it made me wonder, what makes for a good role model? Do role models need to be the same race, gender, and/or sexual orientation as those looking up to them? I don’t know the answer to that, but I do know one thing that I have learned, in terms of good mentoring—that it’s more important to teach your students how to deal with failures than how to deal with successes; good mentors will tell their students about their own failures and not their successes. I feel this is especially important and true for minority students, who come to the table often lacking the self-confidence that others have. And by the way, one thing I want to announce is that this morning, at the board of directors meeting, I am delighted to tell you that we unanimously agreed to have a new ASHG award for mentorship. I feel this is long overdue. In conclusion:(1)We have made advances when it comes to diversity, especially for women, but not really as much when it comes to racial diversity.(2)I do believe that mentoring is key to advancing diversity.(3)Advances in genomic technology are changing the way we study disease etiology as we transition from gene discovery to diagnosis and treatments, but families are still important both in research and in the clinic, and this is true for both genetic and non-genetic reasons.(4)Social justice and equality are normative values. Genetic arguments have no place in the fight for social justice and equality. Now, you all heard the tune at the beginning, and I gave you a warning. So there is going to be a sing-along. I am going to show you the words (which are not the same as in the original version), and I want you to sing along with me because I’m losing my voice here. (To the tune of “Those Were the Days,” written by Gene Raskin):The way we did the TDTMapping genes by IBDFounder pops our cup of teaThose were the daysSegregation and linkage tooFamily based the thing to doWe could use a tool like GeneHunter-Plus againDidn’t need no BiomekAll pipetting done by techGee our old LaSalle ran great(Sorry, I know that doesn’t rhyme—I just wanted to see that car again!)Those were the days!!!!! Finis. Download .pdf (.15 MB) Help with pdf files Document S1. Table S1