The origins of individual differences in socioeconomic outcomes, including educational attainment and occupational status, reflect a combination of genetic and environmental factors whose relative contributions may shift across historical and societal contexts. Previous research suggested a doubling of genetic influence on these traits in independent Estonia compared to the Soviet era. Using the Estonian Biobank, now tenfold larger compared to the original study, we aimed to replicate and extend these findings. We found only limited evidence for the increase in genetic influence on social outcomes in independent Estonia with results differing between analytical setups. Most importantly, we show that genetic contribution to socioeconomic outcomes, as well as to height and body mass index, varies within each historical cohort depending on birth year and recruitment strategy. This highlights the limitations of generalising from the study cohort due to various participation biases and potential heterogeneity of social environment in both historical periods. ### Competing Interest Statement The authors have declared no competing interest. Ministry of Education and Research, TK214, TK218 Medical Research Council, UKRI1503 Estonian Research Council, PSG615, PRG1137

Autoimmune hypothyroidism (Hashimoto's thyroiditis) is common and has a strong genetic component. Here we performed multi-ancestry genome-wide association meta-analyses encompassing 48,694 Hashimoto's thyroiditis cases, using a precise case definition, and 1,044,134 controls. We identified 155 significant (P < 5 × 10-8) independent genetic associations, of which 45 variants and 19 loci were not previously associated with hypothyroidism. Six loci were specific for individuals of European ancestry reference populations. Functional enrichment analyses of Hashimoto's thyroiditis-associated genes highlighted immune cells and the spleen, underpinning the importance of T cells in Hashimoto's thyroiditis development. This observation was further supported by 161 significant colocalizations with expression quantitative trait loci in immune cells and 40 in thyroid tissue (for example, TG, VAV3, IRF5), highlighting the interplay between the immune system and the thyroid. Mendelian randomization indicated causal effects of Hashimoto's thyroiditis on cardiovascular traits and expected associations with thyroid hormone levels.

In this Comment, we outline the Nordic AI-Health Initiative platform, built on unique large-scale longitudinal and multimodal health data sets from across the region. The platform is designed to enable secure, regulation-compliant access and to deliver generalizable models for responsible AI-driven discovery in medicine.

BACKGROUND:Food allergy (FA) arises from a complex interplay between an individual's genetic predisposition and environmental factors, and its prevalence is increasing. Genome-wide association studies to date have been hindered by small sample sizes and varying FA definitions. OBJECTIVE:We sought to identify novel FA risk loci by conducting a genome-wide association study meta-analysis in children and adults by using a multiphenotype approach to ensure a good trade-off between sufficient sample size and valid FA definitions. METHODS:Analyses were conducted separately in children and adults on the basis of the following FA phenotypes: self-report, doctor diagnosis, food-specific sensitization, and doctor diagnosis plus food-specific sensitization. A meta-analysis was performed of genome-wide association studies from up to 16 cohorts of people of European ancestry including 229,426 adults and 14,234 children. Models were adjusted for sex, age, principal components, and, if applicable, further study-specific confounders. Sensitivity models were additionally adjusted for hay fever. Replication was conducted in additional external cohorts and a validation in oral food challenge-defined FA cases. RESULTS:Thirty-seven single nucleotide polymorphisms met suggestive significance (P < 1 × 10-6), with two reaching genome-wide significance: rs116936231 (FGL1) in adult doctor-diagnosed FA plus food-specific sensitization phenotype (stable after additional hay fever adjustment) and rs8022829 (AKAP6-NPAS3), which was significant only in the hay fever-adjusted model in adults. However, neither variant was validated. Further, we identified 3 single nucleotide polymorphisms previously reported for FA and atopic disease. CONCLUSION:This study identified 37 single nucleotide polymorphisms suggestively associated with FA and demonstrated genetic differences across phenotypes. It highlights the need for a unified FA definition and sheds light on FA's shared genetic architecture with allergies.

Summary Background Amiodarone is a widely used antiarrhythmic which frequently induces thyroid dysfunction, including both amiodarone-induced hypothyroidism (AIH) and thyrotoxicosis (AIT). Whether genetic factors contribute to these adverse drug reactions is unknown. In this study, we aimed to identify genetic variants that influence the risk of amiodarone-induced thyroid dysfunction and to evaluate their potential to support genotype-guided risk screening. Methods This pharmacogenetic study comprised two genome-wide meta-analyses of AIH and AIT using five datasets (Copenhagen Hospital Biobank, The Danish Blood Donor Study, Estonian Biobank, deCODE genetics, and Mass General Brigham Biobank). Key measures included the odds ratio (OR) per risk allele, the variants’ effects on spontaneous thyroid disease and biomarkers, and their clinical predictive ability, assessed by the area under the receiver operating curve (AUC), positive and negative predictive values (PPV and NPV). Findings The AIH meta-analysis (880 cases, 4,031 controls) identified three genome-wide significant loci in: FOXE1 (rs36052460; OR 2.58, allele frequency [AF] = 64.3%, P = 2.55 × 10 −44 ), FOXA2 (rs2424459; OR 1.67, AF = 71.3%, P = 2.59 × 10 −14 ), and ADAM32 (rs12681571; OR 1.49, AF = 61.8%, P = 3.05 × 10 −9 ). The AIT meta-analysis (385 cases, 4,936 controls) identified one locus in CAPZB (rs867355; OR 1.63, AF = 66.1%, P = 3.49 × 10 −8 ). In risk prediction models, a polygenic risk score (PRS) of the AIH variants increased the AUC by 9.2% (95% CI 6.6 – 11.9%), which outperformed a genome-wide hypothyroidism PRS (1.5% AUC increase, 95%CI 0.0 – 2.9%). Similarly, the CAPZB variant improved AIT prediction (AUC increase of 4.0%, 95% CI 0.4 – 7.5%) beyond a hyperthyroidism PRS (0.2% AUC increase, 95%CI -0.8 – 1.2%). Genotype-guided screening would identify individuals at low risk (NPVs ranging from 90-95% and PPVs 2-20%). Interpretation We identified genetic variants that influence the risk of developing amiodarone-induced thyroid dysfunction. Genotype-guided screening offers a potential complement to current strategies and personalize pre-treatment risk assessment for patients initiating amiodarone therapy.

Pre-existing psychiatric disorders have been associated with the severity of acute respiratory infections, including COVID-19, particularly in hospitalized populations. However, the underlying mechanisms, especially in community-based populations, remain unknown, limiting preparedness for future pandemics. We investigated the role of genetic liability for psychiatric disorders and related traits in COVID-19 and other respiratory infection severity among individuals reporting SARS-CoV-2 testing and available respiratory symptom data. We included population-based cohort data from Denmark, Estonia, Iceland, Norway, and the United Kingdom (N = 78,507; 62

Dilated cardiomyopathy (DCM) is a heart condition characterized by systolic and diastolic dysfunction. In many instances, patients with DCM coexist with obesity and sleep apnea. It is unclear whether genetic variants contribute to the combined phenotypes of DCM, obesity, and sleep apnea. Here, using next-generation sequencing, we identified pathogenic KCNA2 variants in patients of diverse ancestry with DCM, Obesity, and Sleep Apnea (termed DOSA). Electrophysiological and biochemical assays using biosensors revealed loss of membrane current due to trafficking defects in cells expressing KCNA2 variants. Furthermore, cellular models including patient-specific iPSC cardiomyocytes and organoid models displayed RAC1-ERK1/2 hyperactivation in disease pathogenesis. A Drosophila model expressing KCNA2 variant showed DOSA-like phenotypes which was rescued using RAC1 inhibitors. Our results provide the first evidence that KCNA2 variants can lead to DOSA phenotypes, further expanding the genetic regulatory roles of potassium channels in human diseases.

Refractive errors (REs) affect over half of the global population, with consequences ranging from blurred vision to blindness. Here we conducted ancestry-stratified and cross-ancestry meta-analyses of genome-wide association studies for RE in people of European (n = 1,495,159), East Asian (n = 121,172) and African (n = 144,737) ancestries. The cross-ancestry meta-analysis identified 932 RE-associated variants, including 241 previously unknown associations, four East Asian-specific associations and one African-specific association. Statistical fine-mapping pinpointed 16 high-confidence putative causal variants, and gene prioritization analyses highlighted 23 genes involved in eye development. We constructed an enhanced polygenic predictor incorporating functional annotations that explained 21.4% of RE variation, effectively stratified the onset, progression and severity of myopia, and achieved an area under the receiver operating characteristic curve of 0.806 for predicting high myopia. Our multi-ancestry genome-wide association study expands substantially the catalog of genetic variants for RE and demonstrates the potential clinical utility of polygenic prediction in identifying high-risk people across diverse populations.

Panic disorder is an anxiety disorder with poorly understood etiology. Although twin studies suggest modest heritability (~40%), few genetic variants have been associated with it. We carried out a genome-wide association study in the Finnish longitudinal health register-based FinnGen study to identify genetic variants that predispose to panic disorder. FinnGen cases (N=3,549) were defined as individuals with an ICD-10 or ICD-9 lifetime diagnosis of panic disorder. Control subjects (N=159,869) were free of any psychiatric diagnoses. We identified a locus on chromosome 10q25.1 within SORCS3 that was significantly associated with panic disorder. The minor allele (T; frequency 21%) of the lead variant rs902306 increased the risk of panic disorder by 22% (OR=1.22, 95% CI=1.15-1.30, p-value=1.1x10-10). We also investigated serum SORCS3 protein levels in 107 panic disorder cases with or without agoraphobia and 95 controls free of axis I psychiatric disorders collected at the Anxiety Disorders Outpatient Unit of the Max Planck Institute of Psychiatry. Serum SORCS3 levels were 41% higher in panic disorder cases compared to controls (beta=0.694, SE=0.141, p-value=8.7x10-07). This finding replicated in 84 subjects from an independent German clinical panic disorder sample (beta=1.137, SE=0.532, p-value=0.04), but not in plasma samples of Finnish panic disorder patients from a biobank. Overall, SORCS3 is a novel panic disorder locus, which has previously been associated with other psychiatric and neurodevelopmental disorders. SORCS3 belongs to the sortilin family, with multiple functions related to brain plasticity. Characterization of its role in panic disorder will increase understanding of the neurobiological mechanisms involved in anxiety. ### Competing Interest Statement IH, AE, and CWT are listed as inventors on a patent filed by the University of Helsinki and Max Planck Institute of Psychiatry on the use of serum SORCS3 levels as a biomarker for panic disorder. The other authors report no conflicts of interest. ### Funding Statement This work was funded by the Sigrid Juselius Foundation (IH), Max Planck Society (EB, CWT, BN, AEL), German Research Foundation (AP, RP, JBL) and the EU ERDF grant no. 2014-2020.4.01.15-0012 (MV, AM, Estonian Center of Excellence in Genomics and Translational Medicine). The UKBB replication study has been conducted using the UK Biobank Resource under application number 31063. The FinnGen project is funded by two grants from Business Finland (HUS 4685/31/2016 and UH 4386/31/2016) and the following industry partners: AbbVie Inc., AstraZeneca UK Ltd, Biogen MA Inc., Bristol Myers Squibb (and Celgene Corporation & Celgene International II Sarl), Genentech Inc., Merck Sharp & Dohme LCC, Pfizer Inc., GlaxoSmithKline Intellectual Property Development Ltd., Sanofi US Services Inc., Maze Therapeutics Inc., Janssen Biotech Inc, Novartis AG, and Boehringer Ingelheim International GmbH. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The FinnGen Study was approved by the Coordinating Ethics Committee of the Hospital District of Helsinki and Uusimaa (HUS). The UK Biobank Study was approved by the North West Multi-centre Research Ethics Committee. The Max Planck Institute of Psychiatry study was approved by the ethics committee of Ludwig-Maximilians-University in Munich. The University Hospital of Wuerzburg ethical committee approved the University of Wuerzburg study. The Helsinki Biobank Study Sample was approved by the Helsinki University Hospital Ethics Committee (22/2023). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Genome-wide association studies (GWAS) have discovered thousands of replicable genetic associations, guiding drug target discovery and powering genetic prediction of human phenotypes and diseases. However, genetic associations can be affected by gene-environment correlations and non-random mating, which can lead to biased inferences in downstream analyses. Family-based GWAS (FGWAS) uses the natural experiment of random assignment of genotype within families to separate out the contribution of direct genetic effects (DGEs) - causal effects of alleles in an individual on an individual - from other factors contributing to genetic associations. Here, we report results from an FGWAS meta-analysis of 34 phenotypes from 17 cohorts. We found evidence that factors uncorrelated with DGEs make substantial contributions to genetic associations for 27 phenotypes, with population stratification confounding - a form of gene-environment correlation - likely the major cause. By estimating SNP heritability and genetic correlations using DGEs, we found evidence that assortative mating has led to overestimation of SNP heritability for 5 phenotypes and overestimation of the degree of shared genetic effects (pleiotropy) between 22 pairs of phenotypes. Polygenic predictors constructed from DGEs are particularly useful for studying natural selection, assortative mating, and indirect genetic effects (effects of relatives' genes mediated through the family environment). We validate our meta-analysis results by predicting phenotypes in hold-out samples using polygenic predictors constructed from DGEs, achieving statistically significant out-of-sample prediction for 24 phenotypes with little attenuation of predictive power within-families. We provide FGWAS summary statistics for 34 phenotypes that can be used for downstream analyses. Our study provides both a template for performing FGWAS and an argument for its value for debiasing inferences and understanding the impact of environment and mating patterns.

Circulating miRNAs have emerged as promising biomarker candidates due to their stability and their role in regulating key pathological pathways in cardiovascular disease (CVD). Yet, large-scale, multicentre studies examining their diagnostic and prognostic potential are scarce. This study evaluates the potential of miRNA expression profiles to inform disease classification and risk stratification across major CVD phenotypes, including acute coronary syndrome (ACS), chronic coronary artery disease (CAD), dilated cardiomyopathy (DCM), and ischemic cardiomyopathy (ICM), in a large, multicentre European cohort. We assessed genome-wide miRNA expression profiles in a total of 1209 cardiovascular patients and 848 controls in a uniform, standardized fashion, which renders this study one of the largest prospective miRNA studies. To focus on only the most biologically plausible miRNAs for clinical translation, we mined all original studies of miRNA candidates in CVD and performed differential miRNA expression and enrichment analysis. We then trained disease-specific binary classification models to evaluate the diagnostic potential of miRNA signatures. Finally, we evaluated prognosis and disease severity based on distinct miRNA levels. Six hundred thirty four original abstracts were identified, detailing 166 ACS, 181 CAD, 56 DCM, and 182 ICM miRNAs. Without further optimization, the signatures of a priori miRNAs already yielded very good diagnostic performance with ROC AUC of 0.83–0.95. There was an improvement when considering additional miRNAs in a discovery setting. Interestingly, in ACS, CAD, and DCM, we observed a significantly worse prognosis in probands with higher miRNA-derived disease probabilities, indicating an association with prognosis. The European BestAgeing miRNA study reveals emerging associations of several miRNA signatures with cardiovascular disease discrimination and prognostication, providing a foundation for future external validation and potential clinical translation of this class of markers.

OBJECTIVES:Genetic and genomic tests are the cornerstone of personalized preventive approaches. Inconsistency in evaluating their clinical utility is often cited as a reason for their limited implementation in clinical practice. Previous reviews have primarily focused on theoretical frameworks used for clinical utility evaluations of genetic tests, rather than actual assessments and examined dimensions, rather than specific indicators within these dimensions. We aimed to review the dimensions and the specific indicators measured in published assessment reports of genetic or genomic tests. STUDY DESIGN AND SETTING:We conducted a scoping review of assessment reports of genetic and genomic tests used for prevention, searching through PubMed, Web of Science, Scopus, the websites of 20 different organizations, Google, and Google Scholar. From the included assessments, we extracted the reported indicators of clinical utility, compiling a list of disease-specific indicators that detailed their numerator, denominator, and calculation methods. We analyzed the extracted indicators by stratifying them according to ten comprehensive dimensions of clinical utility, the assessment framework used, and the type of indicator (categorized as quantitative, qualitative, reference, or no evidence reported). From these indicators, we then distilled a list of general indicators. RESULTS:We reviewed 3054 unique references and 12,000 results from gray literature searches, ultimately selecting 57 assessment reports. The reference frameworks used were health technology assessment (HTA) (42%), Evaluation of Genomic Applications in Practice and Prevention (EGAPP) (25%), ACCE (21%), and others (12%). We identified 951 disease-specific indicators. The dimensions most frequently evaluated (ie, had at least one indicator) were analytic validity (60%), clinical validity (79%), clinical efficacy (79%), and economic impact (58%). Only 12 assessments compared health outcomes between tested and untested groups, and fewer than 15% of the assessments addressed equity, acceptability, legitimacy, and personal value. CONCLUSION:Our study illustrates that, although dimensions such as equity and acceptability, are significantly emphasized in traditional evaluation frameworks, these are often not considered in the assessments. Additionally, our study has underscored a significant dearth of reported primary evidence concerning the clinical efficacy of these tests. PLAIN LANGUAGE SUMMARY:Genetic and genomic tests analyze a person's genes to predict health risks and guide healthcare decisions, potentially identifying who might benefit from certain treatments or check-ups. However, determining whether these tests are genuinely useful for wide use in health services is complex, because there is no standard way to define "clinical utility" of a genetic test. To understand how these tests are evaluated, we reviewed 57 evaluation reports from high-income countries, most of which focused on cancer-related genetic tests. We found that many evaluations looked mainly at how well a test predicted a condition (validity) and considered some form of effectiveness, yet often failed to measure whether the test truly improved patient health outcomes, such as lowering death rates or enhancing the quality of life. Moreover, factors like patient acceptance, equity, and personal relevance (eg, reducing anxiety) were frequently overlooked. Without including these broader considerations, evaluations risk missing critical evidence that would indicate whether a test is helpful, fair, and worth using. From over 900 unique indicators used to measure clinical utility, we created a simpler list of about 150 general indicators that can guide future evaluations. This consolidated list can help test developers decide which factors to investigate, evaluators determine what to measure, and policymakers identify what might be missing before deciding if a test should be adopted in healthcare. By highlighting the gaps-areas that should be assessed but currently are not-our study encourages a more comprehensive approach to evaluating genetic tests. If we fail to consider issues like equity, patient preferences, and proven health benefits, we risk investing in tests that may do little good or even harm patients. Ultimately, recognizing these shortcomings can lead to better-informed decisions, ensuring that genetic testing is used in ways that truly benefit patients and deliver safer, more personalized, and fairer healthcare for everyone.

Large biobanks have set a new standard for research and innovation in human genomics and implementation of personalized medicine. The Estonian Biobank was founded a quarter of a century ago, and its biological specimens, clinical, health, omics, and lifestyle data have been included in over 800 publications to date. What makes the biobank unique internationally is its translational focus, with active efforts to conduct clinical studies based on genetic findings, and to explore the effects of return of results on participants. In this review, we provide an overview of the Estonian Biobank, highlight its strengths for studying the effects of genetic variation and quantitative phenotypes on health-related traits, development of methods and frameworks for bringing genomics into the clinic, and its role as a driving force for implementing personalized medicine on a national level and beyond.

Over 85% of the population experience acne at some point in their lives, with its severity spanning a quantitative spectrum, from mild, transient outbreaks to more persistent, severe forms of the condition. Moderate to severe disease poses a substantial global burden arising from both the physical and psychological impacts of this highly visible condition. The analytical approach taken in this study aimed to address the impact of variation in the dichotomisation of acne case control status, driven by ascertainment and study design, on effect size estimates across independent genetic association studies of acne. Through a fixed intercept meta-regression framework, we combined evidence genome-wide for association with acne across studies in which case-control status had been ascertained in different settings, allowing for different severity threshold definitions. Across a combined sample of 73,997 cases and 1,103,940 controls of European, South Asian and African American ancestry we identify genetic variation at 165 genomic loci that influence acne risk. There is evidence for both shared and ancestry specific components to the genetic susceptibility to acne and for sex differences in the magnitude of effect of risk alleles at three loci. We observe that common genetic variation explains 13.4% of acne heritability on the liability scale. Consistent with the hypothesis that genetic risk primarily operates at the level of individual pilosebaceous units, a polygenic score derived from this case-control study of acne susceptibility is associated with both self-reported and clinically assessed acne severity in adolescence, further strengthening the link between genetic risk and disease severity. Prioritisation of causal genes at the identified acne risk loci, provides genetic validation of the targets of established and emerging acne therapies, including retinoid treatments. The identified acne risk loci are enriched for genes encoding downstream effectors of RXRA signalling, including SOX9 and components of the WNT and p53 pathways. Illustrating that the control of stem cell lineage plasticity and cellular fate are important mechanisms through which genetic variation influences acne susceptibility within the pilosebaceous unit.

Tick-borne encephalitis (TBE) is a viral infection of the central nervous system, caused by the tick-borne encephalitis virus (TBEV) presenting clinically as meningitis, meningoencephalitis, and meningoencephalomyelitis. To investigate genetic susceptibility to TBE, and its severe forms, we conducted a genome-wide association study in the European population comprising 1,600 TBE cases and 9,699 controls. We identified several suggestive (p < 1 × 10-5) intronic and exonic variants in ABCG1, the only gene significantly associated with TBE susceptibility. These variants were shown to influence ABCG1 expression in peripheral blood, a finding corroborated by RNA expression analysis. In vitro inhibition or silencing of ABCG1 significantly reduced TBEV replication in both neuronal cells and macrophages, highlighting the potential role of ABCG1 in TBEV biology. Additionally, we detected a genome-wide significant variant within TEX41, located downstream of ZEB1, associated with severe forms of TBE. These findings provide novel insights into the genetic factors underlying TBE susceptibility and severity.

We performed a genome-wide meta-analysis of hypothyroidism (113,393 cases and 1,065,268 controls), free thyroxine (191,449 individuals) and thyroid-stimulating hormone (482,873 individuals). We identified 350 loci associated with hypothyroidism, including 179 not previously reported, 29 of which were linked through thyroid-stimulating hormone. We found that many hypothyroidism risk loci regulate blood cell counts and the circulating inflammasome, and through multiple gene-mapping strategies, we prioritized 259 putative causal genes enriched in immune-related functions. We developed a polygenic risk score (PRS) based on more than 115,000 hypothyroidism cases to address diagnostic challenges in individuals with or at risk of thyroid hormone deficiency. We show that the highest predictive accuracy for hypothyroidism was achieved when combining the PRS with thyroid hormones and thyroid-peroxidase autoantibodies, and that the PRS was able to stratify risk of progression among individuals with subclinical hypothyroidism. These findings demonstrate the potential for a hypothyroidism PRS to support the prediction of disease progression and onset in thyroid hormone deficiency.

BACKGROUND:Dopaminergic neuron depletion in the substantia nigra (SN) and the pathological aggregation of α-synuclein are the neuropathological hallmarks of Parkinson's disease (PD). OBJECTIVES:This study aimed to investigate the association between the polygenic risk score for PD (PD-PRS) and transcranial sonography (TCS)-measured SN hyperechogenicity to enhance the accuracy of PD susceptibility prediction. METHODS:PD-PRSs were calculated for over 41,000 Estonian Biobank participants age 55+ years without a PD diagnosis. Participants in the highest and lowest PD-PRS percentiles (n = 222) underwent TCS measurements and Sniffin' sticks olfactory testing. A multivariable logistic regression model was used to examine the associations between PD-PRS, risk and prodromal markers, and SN hyperechogenicity. RESULTS:Data from 204 participants with TCS measurements were analyzed, including 107 individuals in the high-risk PD-PRS group and 97 in the low-risk PD-PRS group. Incorporating PD-PRS group assignment improved the explained variance in SN hyperechogenicity from 17.2% to 31.9%. Participants in the low-risk PD-PRS group had 0.16 times lower odds (95% confidence interval (CI) = 0.07-0.35, P < 0.001) of developing SN hyperechogenicity compared to high-risk PD-PRS individuals. Each unit increase in the Sniffin' sticks olfactory test score was significantly associated with reduced odds of SN hyperechogenicity (adjusted odds ratio = 0.60, 95% CI = 0.47-0.78, P = 0.002). CONCLUSIONS:Our findings indicate that TCS-measured SN hyperechogenicity is associated with PD-PRS and olfactory impairment. This combined assessment may improve early diagnosis of prodromal PD by pinpointing individuals at increased risk.