Genetic drivers and cellular selection of female mosaic X chromosome loss.

Mosaic loss of the X chromosome (mLOX) is the most common clonal somatic alteration in leukocytes of female individuals1,2, but little is known about its genetic determinants or phenotypic consequences. Here, to address this, we used data from 883,574 female participants across 8 biobanks; 12% of participants exhibited detectable mLOX in approximately 2% of leukocytes. Female participants with mLOX had an increased risk of myeloid and lymphoid leukaemias. Genetic analyses identified 56 common variants associated with mLOX, implicating genes with roles in chromosomal missegregation, cancer predisposition and autoimmune diseases. Exome-sequence analyses identified rare missense variants in FBXO10 that confer a twofold increased risk of mLOX. Only a small fraction of associations was shared with mosaic Y chromosome loss, suggesting that distinct biological processes drive formation and clonal expansion of sex chromosome missegregation. Allelic shift analyses identified X chromosome alleles that are preferentially retained in mLOX, demonstrating variation at many loci under cellular selection. A polygenic score including 44 allelic shift loci correctly inferred the retained X chromosomes in 80.7% of mLOX cases in the top decile. Our results support a model in which germline variants predispose female individuals to acquiring mLOX, with the allelic content of the X chromosome possibly shaping the magnitude of clonal expansion.

Thrombosis risk in single- and double-heterozygous carriers of factor V Leiden and prothrombin G20210A in FinnGen and the UK Biobank.

ABSTRACT: The factor V Leiden (FVL; rs6025) and prothrombin G20210A (PTGM; rs1799963) polymorphisms are 2 of the most well-studied genetic risk factors for venous thromboembolism (VTE). However, double heterozygosity (DH) for FVL and PTGM remains poorly understood, with previous studies showing marked disagreement regarding thrombosis risk conferred by the DH genotype. Using multidimensional data from the UK Biobank (UKB) and FinnGen biorepositories, we evaluated the clinical impact of DH carrier status across 937 939 individuals. We found that 662 participants (0.07%) were DH carriers. After adjustment for age, sex, and ancestry, DH individuals experienced a markedly elevated risk of VTE compared with wild-type individuals (odds ratio [OR] = 5.24; 95% confidence interval [CI], 4.01-6.84; P = 4.8 × 10-34), which approximated the risk conferred by FVL homozygosity. A secondary analysis restricted to UKB participants (N = 445 144) found that effect size estimates for the DH genotype remained largely unchanged (OR = 4.53; 95% CI, 3.42-5.90; P < 1 × 10-16) after adjustment for commonly cited VTE risk factors, such as body mass index, blood type, and markers of inflammation. In contrast, the DH genotype was not associated with a significantly higher risk of any arterial thrombosis phenotype, including stroke, myocardial infarction, and peripheral artery disease. In summary, we leveraged population-scale genomic data sets to conduct, to our knowledge, the largest study to date on the DH genotype and were able to establish far more precise effect size estimates than previously possible. Our findings indicate that the DH genotype may occur as frequently as FVL homozygosity and may confer a similarly increased risk of VTE.

Genetic contribution to disease-course severity and progression in the SUPER-Finland study, a cohort of 10,403 individuals with psychotic disorders.

Genetic factors contribute to the susceptibility of psychotic disorders, but less is known how they affect psychotic disease-course development. Utilizing polygenic scores (PGSs) in combination with longitudinal healthcare data with decades of follow-up we investigated the contributing genetics to psychotic disease-course severity and diagnostic shifts in the SUPER-Finland study, encompassing 10 403 genotyped individuals with a psychotic disorder. To longitudinally track the study participants' past disease-course severity, we created a psychiatric hospitalization burden metric using the full-coverage and nation-wide Finnish in-hospital registry (data from 1969 and onwards). Using a hierarchical model, ranking the psychotic diagnoses according to clinical severity, we show that high schizophrenia PGS (SZ-PGS) was associated with progression from lower ranked psychotic disorders to schizophrenia (OR = 1.32 [1.23-1.43], p = 1.26e-12). This development manifested already at psychotic illness onset as a higher psychiatric hospitalization burden, the proxy for disease-course severity. In schizophrenia (n = 5 479), both a high SZ-PGS and a low educational attainment PGS (EA-PGS) were associated with increased psychiatric hospitalization burden (p = 1.00e-04 and p = 4.53e-10). The SZ-PGS and the EA-PGS associated with distinct patterns of hospital usage. In individuals with high SZ-PGS, the increased hospitalization burden was composed of longer individual hospital stays, while low EA-PGS associated with shorter but more frequent hospital visits. The negative effect of a low EA-PGS was found to be partly mediated via substance use disorder, a major risk factor for hospitalizations. In conclusion, we show that high SZ-PGS and low EA-PGS both impacted psychotic disease-course development negatively but resulted in different disease-course trajectories.

Genome-wide association studies highlight novel risk loci for septal defects and left-sided congenital heart defects.

BACKGROUND: Congenital heart defects (CHD) are structural defects of the heart affecting approximately 1% of newborns. They exhibit low penetrance and non-Mendelian patterns of inheritance as varied and complex traits. While genetic factors are known to play an important role in the development of CHD, the specific genetics remain unknown for the majority of patients. To elucidate the underlying genetic risk, we performed a genome wide association study (GWAS) of CHDs in general and specific CHD subgroups using the FinnGen Release 10 (R10) (N > 393,000), followed by functional fine-mapping through eQTL and co-localization analyses using the GTEx database. RESULTS: We discovered three genome-wide significant loci associated with general CHD. Two of them were located in chromosome 17: 17q21.32 (rs2316327, intronic: LRRC37A2, Odds ratio (OR) [95% Confidence Interval (CI)] = 1.17[1.12-1.23], p = 1.5 × 10-9) and 17q25.3 (rs1293973611, nearest: BAHCC1, OR[95%CI] = 4.48[2.80-7.17], p = 7.0 × 10-10), respectively, and in addition to general CHD, the rs1293973611 locus was associated with the septal defect subtype. The third locus was in band 1p21.2 (rs35046143, nearest: PALMD, OR[95%CI] = 1.15[1.09-1.21], p = 7.1 × 10-9), and it was associated with general CHD and left-sided lesions. In the subgroup analysis, two additional loci were associated with septal defects (rs75230966 and rs6824295), and one with left-sided lesions (rs1305393195). In the eQTL analysis the variants rs2316327 (general CHD), and rs75230966 (septal defects) both located in 17q21.32 (with a LD r2 of 0.41) were both predicted to significantly associate with the expression of WNT9B in the atrial appendage tissue category. This effect was further confirmed by co-localization analysis, which also implicated WNT3 expression in the atrial appendage. A meta-analysis of general CHD together with the UK Biobank (combined N = 881,678) provided a different genome-wide significant locus in LRRC37A2; rs16941382 (OR[95%CI] = 1.15[1.11-1.20], p = 1.5 × 10-9) which is in significant LD with rs2316327. CONCLUSIONS: Our results of general CHD and different CHD subcategories identified a complex risk locus on chromosome 17 near BAHCC1 and LRRC37A2, interacting with the genes WNT9B, WNT3 and MYL4, may constitute potential novel CHD risk associated loci, warranting future experimental tests to determine their role.

High-Resolution Genotyping of Formalin-Fixed Tissue Accurately Estimates Polygenic Risk Scores in Human Diseases.

Formalin-fixed paraffin-embedded (FFPE) tissues stored in biobanks and pathology archives are a vast but underutilized source for molecular studies on different diseases. Beyond being the "gold standard" for preservation of diagnostic human tissues, FFPE samples retain similar genetic information as matching blood samples, which could make FFPE samples an ideal resource for genomic analysis. However, research on this resource has been hindered by the perception that DNA extracted from FFPE samples is of poor quality. Here, we show that germline disease-predisposing variants and polygenic risk scores (PRS) can be identified from FFPE normal tissue (FFPE-NT) DNA with high accuracy. We optimized the performance of FFPE-NT DNA on a genome-wide array containing 657,675 variants. Via a series of testing and validation phases, we established a protocol for FFPE-NT genotyping with results comparable with blood genotyping. The median call rate of FFPE-NT samples in the validation phase was 99.85% (range 98.26%-99.94%) and median concordance with matching blood samples was 99.79% (range 98.85%-99.9%). We also demonstrated that a rare pathogenic PALB2 genetic variant predisposing to cancer can be correctly identified in FFPE-NT samples. We further imputed the FFPE-NT genotype data and calculated the FFPE-NT genome-wide PRS in 3 diseases and 4 disease risk variables. In all cases, FFPE-NT and matching blood PRS were highly concordant (all Pearson's r > 0.95). The ability to precisely genotype FFPE-NT on a genome-wide array enables translational genomics applications of archived FFPE-NT samples with the possibility to link to corresponding phenotypes and longitudinal health data.

Polygenic risk scores as a marker for epilepsy risk across lifetime and after unspecified seizure events.

A diagnosis of epilepsy has significant consequences for an individual but is often challenging in clinical practice. Novel biomarkers are thus greatly needed. Here, we investigated how common genetic factors (epilepsy polygenic risk scores, [PRSs]) influence epilepsy risk in detailed longitudinal electronic health records (EHRs) of > 700k Finns and Estonians. We found that a high genetic generalized epilepsy PRS (PRSGGE) increased risk for genetic generalized epilepsy (GGE) (hazard ratio [HR] 1.73 per PRSGGE standard deviation [SD]) across lifetime and within 10 years after an unspecified seizure event. The effect of PRSGGE was significantly larger on idiopathic generalized epilepsies, in females and for earlier epilepsy onset. Analogously, we found significant but more modest focal epilepsy PRS burden associated with non-acquired focal epilepsy (NAFE). Here, we outline the potential of epilepsy specific PRSs to serve as biomarkers after a first seizure event.

Genetic Analysis of Obstructive Sleep Apnea and Its Relationship with Severe COVID-19.

Rationale: Although patients with obstructive sleep apnea (OSA) have a higher risk for coronavirus disease (COVID-19) hospitalization, the causal relationship has remained unexplored. Objectives: To understand the causal relationship between OSA and COVID-19 by leveraging data from vaccination and electronic health records, genetic risk factors from genome-wide association studies, and Mendelian randomization. Methods: We elucidated genetic risk factors for OSA using FinnGen (total N = 377,277), performing genome-wide association. We used the associated variants as instruments for univariate and multivariate Mendelian randomization (MR) analyses and computed absolute risk reduction against COVID-19 hospitalization with or without vaccination. Results: We identified nine novel loci for OSA and replicated our findings in the Million Veteran Program. Furthermore, MR analysis showed that OSA was a causal risk factor for severe COVID-19 (P = 9.41 × 10-4). Probabilistic modeling showed that the strongest genetic risk factor for OSA at the FTO locus reflected a signal of higher body mass index (BMI), whereas BMI-independent association was seen with the earlier reported SLC9A4 locus and a MECOM locus, which is a transcriptional regulator with 210-fold enrichment in the Finnish population. Similarly, multivariate MR analysis showed that the causality for severe COVID-19 was driven by BMI (multivariate MR P = 5.97 × 10-6, ß = 0.47). Finally, vaccination reduced the risk for COVID-19 hospitalization more in the patients with OSA than in the non-OSA controls, with respective absolute risk reductions of 13.3% versus 6.3%. Conclusions: Our analysis identified novel genetic risk factors for OSA and showed that OSA is a causal risk factor for severe COVID-19. The effect is predominantly explained by higher BMI and suggests BMI-dependent effects at the level of individual variants and at the level of comorbid causality.

Cardiovascular Significance and Genetics of Epicardial and Pericardial Adiposity.

Importance: Epicardial and pericardial adipose tissue (EPAT) has been associated with cardiovascular diseases such as atrial fibrillation or flutter (AF) and coronary artery disease (CAD), but studies have been limited in sample size or drawn from selected populations. It has been suggested that the association between EPAT and cardiovascular disease could be mediated by local or paracrine effects. Objective: To evaluate the association of EPAT with prevalent and incident cardiovascular disease and to elucidate the genetic basis of EPAT in a large population cohort. Design, Setting, and Participants: A deep learning model was trained to quantify EPAT area from 4-chamber magnetic resonance images using semantic segmentation. Cross-sectional and prospective cardiovascular disease associations were evaluated, controlling for sex and age. Prospective associations were additionally controlled for abdominal visceral adipose tissue (VAT) volumes. A genome-wide association study was performed, and a polygenic score (PGS) for EPAT was examined in independent FinnGen cohort study participants. Data analyses were conducted from March 2022 to December 2023. Exposures: The primary exposures were magnetic resonance imaging-derived continuous measurements of epicardial and pericardial adipose tissue area and visceral adipose tissue volume. Main Outcomes and Measures: Prevalent and incident CAD, AF, heart failure (HF), stroke, and type 2 diabetes (T2D). Results: After exclusions, this study included 44 475 participants (mean [SD] age, 64.1 [7.7] years; 22 972 female [51.7%]) from the UK Biobank. Cross-sectional and prospective cardiovascular disease associations were evaluated for a mean (SD) of 3.2 (1.5) years of follow-up. Prospective associations were additionally controlled for abdominal VAT volumes for 38 527 participants. A PGS for EPAT was examined in 453 733 independent FinnGen cohort study participants. EPAT was positively associated with male sex (ß = +0.78 SD in EPAT; P < 3 × 10-324), age (Pearson r = 0.15; P = 9.3 × 10-229), body mass index (Pearson r = 0.47; P < 3 × 10-324), and VAT (Pearson r = 0.72; P < 3 × 10-324). EPAT was more elevated in prevalent HF (ß = +0.46 SD units) and T2D (ß = +0.56) than in CAD (ß = +0.23) or AF (ß = +0.18). EPAT was associated with incident HF (hazard ratio [HR], 1.29 per +1 SD in EPAT; 95% CI, 1.17-1.43), T2D (HR, 1.63; 95% CI, 1.51-1.76), and CAD (HR, 1.19; 95% CI, 1.11-1.28). However, the associations were no longer significant when controlling for VAT. Seven genetic loci were identified for EPAT, implicating transcriptional regulators of adipocyte morphology and brown adipogenesis (EBF1, EBF2, and CEBPA) and regulators of visceral adiposity (WARS2 and TRIB2). The EPAT PGS was associated with T2D (odds ratio [OR], 1.06; 95% CI, 1.05-1.07; P =3.6 × 10-44), HF (OR, 1.05; 95% CI, 1.04-1.06; P =4.8 × 10-15), CAD (OR, 1.04; 95% CI, 1.03-1.05; P =1.4 × 10-17), AF (OR, 1.04; 95% CI, 1.03-1.06; P =7.6 × 10-12), and stroke in FinnGen (OR, 1.02; 95% CI, 1.01-1.03; P =3.5 × 10-3) per 1 SD in PGS. Conclusions and Relevance: Results of this cohort study suggest that epicardial and pericardial adiposity was associated with incident cardiovascular diseases, but this may largely reflect a metabolically unhealthy adiposity phenotype similar to abdominal visceral adiposity.

Antipsychotic medications and sleep problems in patients with schizophrenia.

BACKGROUND: Sleep problems are common and related to a worse quality of life in patients with schizophrenia. Almost all patients with schizophrenia use antipsychotic medications, which usually increase sleep. Still, the differences in subjective sleep outcomes between different antipsychotic medications are not entirely clear. METHODS: This study assessed 5466 patients with schizophrenia and is part of the nationwide Finnish SUPER study. We examined how the five most common antipsychotic medications (clozapine, olanzapine, quetiapine, aripiprazole, and risperidone) associate with questionnaire-based sleep problems in logistic regression analyses, including head-to-head analyses between different antipsychotic medications. The sleep problems were difficulties initiating sleep, early morning awakenings, fatigue, poor sleep quality, short (≤6 h) and long sleep duration (≥10 h). RESULTS: The average number of antipsychotic medications was 1.59 per patient. Clozapine was associated with long sleep duration (49.0 % of clozapine users vs 30.2 % of other patients, OR = 2.05, 95 % CI 1.83-2.30, p < .001). Olanzapine and risperidone were in head-to-head analyses associated with less sleep problems than patients using aripiprazole, quetiapine, or no antipsychotic medication. Aripiprazole and quetiapine were associated with more insomnia symptoms and poorer sleep quality. Patients without antipsychotic medications (N = 159) had poorer sleep quality than patients with antipsychotic use, and short sleep duration was common (21.5 % of patients not using antipsychotics vs 7.8 % of patients using antipsychotics, OR = 2.97, 95 % CI 1.98-4.44, p < .001). CONCLUSIONS: Prevalence of sleep problems is markedly related to the antipsychotic medication the patient uses. These findings underline the importance of considering and assessing sleep problems when treating schizophrenia patients with antipsychotics.

Genome-wide association study indicates novel associations of annexin A13 to secretory and GAS2L2 with mucous otitis media.

To evaluate the genetics of chronic nonsuppurative otitis media (OM). We performed a genome-wide association study of 429,599 individuals included in the FinnGen study using three different case definitions: combined chronic nonsuppurative OM (7034 cases) (included serous and mucous chronic OM), mucous chronic OM (5953 cases), and secretory chronic OM (1689 cases). Individuals without otitis media were used as controls (417,745 controls). We used immunohistochemistry (IHC) of the murine middle ear to evaluate the expression of annexin A13. Four loci were significantly associated (p < 1.7 × 10-8) with nonsuppurative OM. Three out of the four association signals included missense variants in genes that may play a role in otitis media pathobiology. According to our subtype-specific analyses, one novel locus, located near ANXA13, was associated with secretory OM. Three loci (near TNFRSF13B, GAS2L2, and TBX1) were associated with mucous OM. Immunohistochemistry of murine middle ear samples revealed annexin A13 expression at the apical pole of the Eustachian tube epithelium as well as variable intensity of the secretory cells of the glandular structure in proximity to the Eustachian tube. We demonstrated that secretory and mucous OM have distinct and shared genetic associations. The association of GAS2L2 with ciliary epithelium function and the pathogenesis of dysfunctional mucosa in mucous OM is suggested. The abundant expression of annexin A13 in the Eustachian tube epithelium, along with its role in apical transport for the binding and transfer of phospholipids, indicates the role of annexin A13 and phospholipids in Eustachian tube dysfunction.

Whole-genome sequencing identifies variants in ANK1, LRRN1, HAS1, and other genes and regulatory regions for stroke in type 1 diabetes.

Individuals with type 1 diabetes (T1D) carry a markedly increased risk of stroke, with distinct clinical and neuroimaging characteristics as compared to those without diabetes. Using whole-exome or whole-genome sequencing of 1,051 individuals with T1D, we aimed to find rare and low-frequency genomic variants associated with stroke in T1D. We analysed the genome comprehensively with single-variant analyses, gene aggregate analyses, and aggregate analyses on genomic windows, enhancers and promoters. In addition, we attempted replication in T1D using a genome-wide association study (N = 3,945) and direct genotyping (N = 3,263), and in the general population from the large-scale population-wide FinnGen project and UK Biobank summary statistics. We identified a rare missense variant on SREBF1 exome-wide significantly associated with stroke (rs114001633, p.Pro227Leu, p-value = 7.30 × 10-8), which replicated for hemorrhagic stroke in T1D. Using gene aggregate analysis, we identified exome-wide significant genes: ANK1 and LRRN1 displayed replication evidence in T1D, and LRRN1, HAS1 and UACA in the general population (UK Biobank). Furthermore, we performed sliding-window analyses and identified 14 genome-wide significant windows for stroke on 4q33-34.1, of which two replicated in T1D, and a suggestive genomic window on LINC01500, which replicated in T1D. Finally, we identified a suggestively stroke-associated TRPM2-AS promoter (p-value = 5.78 × 10-6) with borderline significant replication in T1D, which we validated with an in vitro cell-based assay. Due to the rarity of the identified genetic variants, future replication of the genomic regions represented here is required with sequencing of individuals with T1D. Nevertheless, we here report the first genome-wide analysis on stroke in individuals with diabetes.

Distinct and shared genetic architectures of gestational diabetes mellitus and type 2 diabetes.

Gestational diabetes mellitus (GDM) is a common metabolic disorder affecting more than 16 million pregnancies annually worldwide1,2. GDM is related to an increased lifetime risk of type 2 diabetes (T2D)1-3, with over a third of women developing T2D within 15 years of their GDM diagnosis. The diseases are hypothesized to share a genetic predisposition1-7, but few studies have sought to uncover the genetic underpinnings of GDM. Most studies have evaluated the impact of T2D loci only8-10, and the three prior genome-wide association studies of GDM11-13 have identified only five loci, limiting the power to assess to what extent variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen study and identified 13 GDM-associated loci, including nine new loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into the following two distinct categories: one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis and placental expression.

Deep learning of left atrial structure and function provides link to atrial fibrillation risk.

Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to assess the genetic contributions to left atrial structure and function, and understand their relationship with risk for atrial fibrillation. Here, we use deep learning and surface reconstruction models to measure left atrial minimum volume, maximum volume, stroke volume, and emptying fraction in 40,558 UK Biobank participants. In a genome-wide association study of 35,049 participants without pre-existing cardiovascular disease, we identify 20 common genetic loci associated with left atrial structure and function. We find that polygenic contributions to increased left atrial volume are associated with atrial fibrillation and its downstream consequences, including stroke. Through Mendelian randomization, we find evidence supporting a causal role for left atrial enlargement and dysfunction on atrial fibrillation risk.

Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study.

Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.

Evidence for the additivity of rare and common variant burden throughout the spectrum of intellectual disability.

Intellectual disability (ID) is a common disorder, yet there is a wide spectrum of impairment from mild to profoundly affected individuals. Mild ID is seen as the low extreme of the general distribution of intelligence, while severe ID is often seen as a monogenic disorder caused by rare, pathogenic, highly penetrant variants. To investigate the genetic factors influencing mild and severe ID, we evaluated rare and common variation in the Northern Finland Intellectual Disability cohort (n = 1096 ID patients), a cohort with a high percentage of mild ID (n = 550) and from a population bottleneck enriched in rare, damaging variation. Despite this enrichment, we found only a small percentage of ID was due to recessive Finnish-enriched variants (0.5%). A larger proportion was linked to dominant variation, with a significant burden of rare, damaging variation in both mild and severe ID. This rare variant burden was enriched in more severe ID (p = 2.4e-4), patients without a relative with ID (p = 4.76e-4), and in those with features associated with monogenic disorders. We also found a significant burden of common variants associated with decreased cognitive function, with no difference between mild and more severe ID. When we included common and rare variants in a joint model, the rare and common variants had additive effects in both mild and severe ID. A multimodel inference approach also found that common and rare variants together best explained ID status (ΔAIC = 16.8, ΔBIC = 10.2). Overall, we report evidence for the additivity of rare and common variant burden throughout the spectrum of intellectual disability.

TWINGEN: protocol for an observational clinical biobank recall and biomarker cohort study to identify Finnish individuals with high risk of Alzheimer's disease.

INTRODUCTION: A better understanding of the earliest stages of Alzheimer's disease (AD) could expedite the development or administration of treatments. Large population biobanks hold the promise to identify individuals at an elevated risk of AD and related dementias based on health registry information. Here, we establish the protocol for an observational clinical recall and biomarker study called TWINGEN with the aim to identify individuals at high risk of AD by assessing cognition, health and AD-related biomarkers. Suitable candidates were identified and invited to participate in the new study among THL Biobank donors according to TWINGEN study criteria. METHODS AND ANALYSIS: A multi-centre study (n=800) to obtain blood-based biomarkers, telephone-administered and web-based memory and cognitive parameters, questionnaire information on lifestyle, health and psychological factors, and accelerometer data for measures of physical activity, sedentary behaviour and sleep. A subcohort is being asked to participate in an in-person neuropsychological assessment (n=200) and wear an Oura ring (n=50). All participants in the TWINGEN study have genome-wide genotyping data and up to 48 years of follow-up data from the population-based older Finnish Twin Cohort (FTC) study of the University of Helsinki. The data collected in TWINGEN will be returned to THL Biobank from where it can later be requested for other biobank studies such as FinnGen that supported TWINGEN. ETHICS AND DISSEMINATION: This recall study consists of FTC/THL Biobank/FinnGen participants whose data were acquired in accordance with the Finnish Biobank Act. The recruitment protocols followed the biobank protocols approved by Finnish Medicines Agency. The TWINGEN study plan was approved by the Ethics Committee of Hospital District of Helsinki and Uusimaa (number 16831/2022). THL Biobank approved the research plan with the permission no: THLBB2022_83.

A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk.

Polygenic scores (PGSs) offer the ability to predict genetic risk for complex diseases across the life course; a key benefit over short-term prediction models. To produce risk estimates relevant to clinical and public health decision-making, it is important to account for varying effects due to age and sex. Here, we develop a novel framework to estimate country-, age-, and sex-specific estimates of cumulative incidence stratified by PGS for 18 high-burden diseases. We integrate PGS associations from seven studies in four countries (N = 1,197,129) with disease incidences from the Global Burden of Disease. PGS has a significant sex-specific effect for asthma, hip osteoarthritis, gout, coronary heart disease and type 2 diabetes (T2D), with all but T2D exhibiting a larger effect in men. PGS has a larger effect in younger individuals for 13 diseases, with effects decreasing linearly with age. We show for breast cancer that, relative to individuals in the bottom 20% of polygenic risk, the top 5% attain an absolute risk for screening eligibility 16.3 years earlier. Our framework increases the generalizability of results from biobank studies and the accuracy of absolute risk estimates by appropriately accounting for age- and sex-specific PGS effects. Our results highlight the potential of PGS as a screening tool which may assist in the early prevention of common diseases.

High incidence and geographic distribution of cleft palate cases in Finland are associated with a regulatory variant in IRF6.

In Finland the frequency of isolated cleft palate (CP) is higher than that of isolated cleft lip with or without cleft palate (CL/P). This trend contrasts to that in other European countries but its genetic underpinnings are unknown. We performed a genome-wide association study for orofacial clefts, which include CL/P and CP, in the Finnish population. We identified rs570516915, a single nucleotide polymorphism that is highly enriched in Finns and Estonians, as being strongly associated with CP ( P = 5.25 × 10 -34 , OR = 8.65, 95% CI 6.11-12.25), but not with CL/P ( P = 7.2 × 10 -5 ), with genome-wide significance. The risk allele frequency of rs570516915 parallels the regional variation of CP prevalence in Finland, and the association was replicated in independent cohorts of CP cases from Finland ( P = 8.82 × 10 -28 ) and Estonia ( P = 1.25 × 10 -5 ). The risk allele of rs570516915 disrupts a conserved binding site for the transcription factor IRF6 within a previously characterized enhancer upstream of the IRF6 gene. Through reporter assay experiments we found that the risk allele of rs570516915 diminishes the enhancer activity. Oral epithelial cells derived from CRISPR-Cas9 edited induced pluripotent stem cells demonstrate that the CP-associated allele of rs570516915 concomitantly decreases the binding of IRF6 and the expression level of IRF6 , suggesting impaired IRF6 autoregulation as a molecular mechanism underlying the risk for CP.

Proteomic aging clock predicts mortality and risk of common age-related diseases in diverse populations.

Circulating plasma proteins play key roles in human health and can potentially be used to measure biological age, allowing risk prediction for age-related diseases, multimorbidity and mortality. Here we developed a proteomic age clock in the UK Biobank (n = 45,441) using a proteomic platform comprising 2,897 plasma proteins and explored its utility to predict major disease morbidity and mortality in diverse populations. We identified 204 proteins that accurately predict chronological age (Pearson r = 0.94) and found that proteomic aging was associated with the incidence of 18 major chronic diseases (including diseases of the heart, liver, kidney and lung, diabetes, neurodegeneration and cancer), as well as with multimorbidity and all-cause mortality risk. Proteomic aging was also associated with age-related measures of biological, physical and cognitive function, including telomere length, frailty index and reaction time. Proteins contributing most substantially to the proteomic age clock are involved in numerous biological functions, including extracellular matrix interactions, immune response and inflammation, hormone regulation and reproduction, neuronal structure and function and development and differentiation. In a validation study involving biobanks in China (n = 3,977) and Finland (n = 1,990), the proteomic age clock showed similar age prediction accuracy (Pearson r = 0.92 and r = 0.94, respectively) compared to its performance in the UK Biobank. Our results demonstrate that proteomic aging involves proteins spanning multiple functional categories and can be used to predict age-related functional status, multimorbidity and mortality risk across geographically and genetically diverse populations.

Genetic and functional analysis of Raynaud's syndrome implicates loci in vasculature and immunity.

Raynaud's syndrome is a dysautonomia where exposure to cold causes vasoconstriction and hypoxia, particularly in the extremities. We performed meta-analysis in four cohorts and discovered eight loci (ADRA2A, IRX1, NOS3, ACVR2A, TMEM51, PCDH10-DT, HLA, and RAB6C) where ADRA2A, ACVR2A, NOS3, TMEM51, and IRX1 co-localized with expression quantitative trait loci (eQTLs), particularly in distal arteries. CRISPR gene editing further showed that ADRA2A and NOS3 loci modified gene expression and in situ RNAscope clarified the specificity of ADRA2A in small vessels and IRX1 around small capillaries in the skin. A functional contraction assay in the cold showed lower contraction in ADRA2A-deficient and higher contraction in ADRA2A-overexpressing smooth muscle cells. Overall, our study highlights the power of genome-wide association testing with functional follow-up as a method to understand complex diseases. The results indicate temperature-dependent adrenergic signaling through ADRA2A, effects at the microvasculature by IRX1, endothelial signaling by NOS3, and immune mechanisms by the HLA locus in Raynaud's syndrome.