FinnGen provides genetic insights from a well-phenotyped isolated population.

Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10-11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.

Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning.

Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (ß coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks.

Systematic comparison of family history and polygenic risk across 24 common diseases.

Family history is the standard indirect measure of inherited susceptibility in clinical care, whereas polygenic risk scores (PRSs) have more recently demonstrated potential for more directly capturing genetic risk in many diseases. Few studies have systematically compared how these overlap and complement each other across common diseases. Within FinnGen (N = 306,418), we leverage family relationships, up to 50 years of nationwide registries, and genome-wide genotyping to examine the interplay of family history and genome-wide PRSs. We explore the dynamic for three types of family history across 24 common diseases: first- and second-degree family history and parental causes of death. Covering a large proportion of the burden of non-communicable diseases in adults, we show that family history and PRS are independent and not interchangeable measures, but instead provide complementary information on inherited disease susceptibility. The PRSs explained on average 10% of the effect of first-degree family history, and first-degree family history 3% of PRSs, and PRS effects were independent of both early- and late-onset family history. The PRS stratified the risk similarly in individuals with and without family history. In most diseases, including coronary artery disease, glaucoma, and type 2 diabetes, a positive family history with a high PRS was associated with a considerably elevated risk, whereas a low PRS compensated completely for the risk implied by positive family history. This study provides a catalogue of risk estimates for both family history of disease and PRSs and highlights opportunities for a more comprehensive way of assessing inherited disease risk across common diseases.

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.

Genome-wide polygenic risk scores for colorectal cancer have implications for risk-based screening.

BACKGROUND: Hereditary factors, including single genetic variants and family history, can be used for targeting colorectal cancer (CRC) screening, but limited data exist on the impact of polygenic risk scores (PRS) on risk-based CRC screening. METHODS: Using longitudinal health and genomics data on 453,733 Finnish individuals including 8801 CRC cases, we estimated the impact of a genome-wide CRC PRS on CRC screening initiation age through population-calibrated incidence estimation over the life course in men and women. RESULTS: Compared to the cumulative incidence of CRC at age 60 in Finland (the current age for starting screening in Finland), a comparable cumulative incidence was reached 5 and 11 years earlier in persons with high PRS (80-99% and >99%, respectively), while those with a low PRS (< 20%) reached comparable incidence 7 years later. The PRS was associated with increased risk of post-colonoscopy CRC after negative colonoscopy (hazard ratio 1.76 per PRS SD, 95% CI 1.54-2.01). Moreover, the PRS predicted colorectal adenoma incidence and improved incident CRC risk prediction over non-genetic risk factors. CONCLUSIONS: Our findings demonstrate that a CRC PRS can be used for risk stratification of CRC, with further research needed to optimally integrate the PRS into risk-based screening.

Patterns of reproductive health in inflammatory rheumatic diseases and other immune-mediated diseases: a nationwide registry study.

OBJECTIVES: Rheumatic diseases may impair reproductive success and pregnancy outcomes, but systematic evaluations across diseases are lacking. We conducted a nationwide cohort study to examine the impact of rheumatic diseases on reproductive health measures, comparing the impacts with those of other immune-mediated diseases (IMDs). METHODS: Out of all of the 5 339 804 Finnish citizens, individuals born 1964-1984 and diagnosed with any of the 19 IMDs before age 30 (women) or 35 (men) were matched with 20 controls by birth year, sex, and education. We used data from nationwide health registers to study the impact of IMDs on reproductive health measures, such as reproductive success and, for women, ever having experienced adverse maternal and perinatal outcomes. RESULTS: Several of the rheumatic diseases, particularly SLE, JIA, and seropositive RA, were associated with higher rates of childlessness and fewer children. The risks for pre-eclampsia, newborns being small for gestational age, preterm delivery, non-elective Caesarean sections, and need of neonatal intensive care were increased in many IMDs. Particularly, SLE, SS, type 1 diabetes, and Addison's disease showed >2-fold risks for some of these outcomes. In most rheumatic diseases, moderate (1.1-1.5-fold) risk increases were observed for diverse adverse pregnancy outcomes, with similar effects in IBD, celiac disease, asthma, ITP, and psoriasis. CONCLUSION: Rheumatic diseases have a broad impact on reproductive health, with effects comparable with that of several other IMDs. Of the rheumatic diseases, SLE and SS conferred the largest risk increases on perinatal adverse event outcomes.

Polygenic burden has broader impact on health, cognition, and socioeconomic outcomes than most rare and high-risk copy number variants.

Copy number variants (CNVs) are associated with syndromic and severe neurological and psychiatric disorders (SNPDs), such as intellectual disability, epilepsy, schizophrenia, and bipolar disorder. Although considered high-impact, CNVs are also observed in the general population. This presents a diagnostic challenge in evaluating their clinical significance. To estimate the phenotypic differences between CNV carriers and non-carriers regarding general health and well-being, we compared the impact of SNPD-associated CNVs on health, cognition, and socioeconomic phenotypes to the impact of three genome-wide polygenic risk score (PRS) in two Finnish cohorts (FINRISK, n = 23,053 and NFBC1966, n = 4895). The focus was on CNV carriers and PRS extremes who do not have an SNPD diagnosis. We identified high-risk CNVs (DECIPHER CNVs, risk gene deletions, or large [>1 Mb] CNVs) in 744 study participants (2.66%), 36 (4.8%) of whom had a diagnosed SNPD. In the remaining 708 unaffected carriers, we observed lower educational attainment (EA; OR = 0.77 [95% CI 0.66-0.89]) and lower household income (OR = 0.77 [0.66-0.89]). Income-associated CNVs also lowered household income (OR = 0.50 [0.38-0.66]), and CNVs with medical consequences lowered subjective health (OR = 0.48 [0.32-0.72]). The impact of PRSs was broader. At the lowest extreme of PRS for EA, we observed lower EA (OR = 0.31 [0.26-0.37]), lower-income (OR = 0.66 [0.57-0.77]), lower subjective health (OR = 0.72 [0.61-0.83]), and increased mortality (Cox's HR = 1.55 [1.21-1.98]). PRS for intelligence had a similar impact, whereas PRS for schizophrenia did not affect these traits. We conclude that the majority of working-age individuals carrying high-risk CNVs without SNPD diagnosis have a modest impact on morbidity and mortality, as well as the limited impact on income and educational attainment, compared to individuals at the extreme end of common genetic variation. Our findings highlight that the contribution of traditional high-risk variants such as CNVs should be analyzed in a broader genetic context, rather than evaluated in isolation.

Plasma proteins, cognitive decline, and 20-year risk of dementia in the Whitehall II and Atherosclerosis Risk in Communities studies.

INTRODUCTION: Plasma proteins affect biological processes and are common drug targets but their role in the development of Alzheimer's disease and related dementias remains unclear. We examined associations between 4953 plasma proteins and cognitive decline and risk of dementia in two cohort studies with 20-year follow-ups. METHODS: In the Whitehall II prospective cohort study proteins were measured using SOMAscan technology. Cognitive performance was tested five times over 20 years. Linkage to electronic health records identified incident dementia. The results were replicated in the Atherosclerosis Risk in Communities (ARIC) study. RESULTS: Fifteen non-amyloid/non-tau-related proteins were associated with cognitive decline and dementia, were consistently identified in both cohorts, and were not explained by known dementia risk factors. Levels of six of the proteins are modifiable by currently approved medications for other conditions. DISCUSSION: This study identified several plasma proteins in dementia-free people that are associated with long-term risk of cognitive decline and dementia.

Genetic analysis of obstructive sleep apnoea discovers a strong association with cardiometabolic health.

There is currently limited understanding of the genetic aetiology of obstructive sleep apnoea (OSA). We aimed to identify genetic loci associated with OSA risk, and to test if OSA and its comorbidities share a common genetic background.We conducted the first large-scale genome-wide association study of OSA using the FinnGen study (217 955 individuals) with 16 761 OSA patients identified using nationwide health registries.We estimated 0.08 (95% CI 0.06-0.11) heritability and identified five loci associated with OSA (p<5.0×10-8): rs4837016 near GAPVD1 (GTPase activating protein and VPS9 domains 1), rs10928560 near CXCR4 (C-X-C motif chemokine receptor type 4), rs185932673 near CAMK1D (calcium/calmodulin-dependent protein kinase ID) and rs9937053 near FTO (fat mass and obesity-associated protein; a variant previously associated with body mass index (BMI)). In a BMI-adjusted analysis, an association was observed for rs10507084 near RMST/NEDD1 (rhabdomyosarcoma 2 associated transcript/NEDD1 γ-tubulin ring complex targeting factor). We found high genetic correlations between OSA and BMI (rg=0.72 (95% CI 0.62-0.83)), and with comorbidities including hypertension, type 2 diabetes, coronary heart disease, stroke, depression, hypothyroidism, asthma and inflammatory rheumatic disease (rg>0.30). The polygenic risk score for BMI showed 1.98-fold increased OSA risk between the highest and the lowest quintile, and Mendelian randomisation supported a causal relationship between BMI and OSA.Our findings support the causal link between obesity and OSA, and the joint genetic basis between OSA and comorbidities.

Lifetime risk of rheumatoid arthritis-associated interstitial lung disease in MUC5B mutation carriers.

OBJECTIVES: To estimate lifetime risk of developing rheumatoid arthritis-associated interstitial lung disease (RA-ILD) with respect to the strongest known risk factor for pulmonary fibrosis, a MUC5B promoter variant. METHODS: FinnGen is a collection of epidemiological cohorts and hospital biobank samples, integrating genetic data with up to 50 years of follow-up within nationwide registries in Finland. Patients with RA and ILD were identified from the Finnish national hospital discharge, medication reimbursement and cause-of-death registries. We estimated lifetime risks of ILD by age 80 with respect to the common variant rs35705950, a MUC5B promoter variant. RESULTS: Out of 293 972 individuals, 1965 (0.7%) developed ILD by age 80. Among all individuals in the dataset, MUC5B increased the risk of ILD with a HR of 2.44 (95% CI: 2.22 to 2.68). Out of 6869 patients diagnosed with RA, 247 (3.6%) developed ILD. In patients with RA, MUC5B was a strong risk factor of ILD with a HR similar to the full dataset (HR: 2.27, 95% CI: 1.75 to 2.95). In patients with RA, lifetime risks of ILD were 16.8% (95% CI: 13.1% to 20.2%) for MUC5B carriers and 6.1% (95% CI: 5.0% to 7.2%) for MUC5B non-carriers. The difference between risks started to emerge at age 65, with a higher risk among men. CONCLUSION: Our findings provide estimates of lifetime risk of RA-ILD based on MUC5B mutation carrier status, demonstrating the potential of genomics for risk stratification of RA-ILD.

[Medical intern or locum doctor--does job position affect learning?]. / Amanuenssi vai viransijainen--vaikuttaako työsuhde oppimiseen?

At the University of Helsinki, the licentiate degree in medicine involves internships that can be conducted as a medical intern or locum doctor. The students and their supervisors fill out a feedback form, which helps in assessing the students' improvement in various areas. Based on the feedback form between 2008 and 2013, students having worked as locum doctor rated better improvement in their diagnostic skills, writing medical records, interacting with the patient, and operating in the work community. Supervisor evaluations did not show a similar clear difference between the job positions.

Genetics of sleep medication purchases suggests causality from sleep problems to psychiatric traits.

STUDY OBJECTIVES: Over 10% of the population in Europe and in the United States use sleep medication to manage sleep problems. Our objective was to elucidate genetic risk factors and clinical correlates that contribute to sleep medication purchase and estimate the comorbid impact of sleep problems. METHODS: We performed epidemiological analysis for psychiatric diagnoses, and genetic association studies of sleep medication purchase in 797 714 individuals from FinnGen Release 7 (N = 311 892) and from the UK Biobank (N = 485 822). Post-association analyses included genetic correlation, co-localization, Mendelian randomization (MR), and polygenic risk estimation. RESULTS: In a GWAS we identified 27 genetic loci significantly associated with sleep medication, located in genes associated with sleep; AUTS2, CACNA1C, MEIS1, KIRREL3, PAX8, GABRA2, psychiatric traits; CACNA1C, HIST1H2BD, NUDT12. TOPAZ1 and TSNARE1. Co-localization and expression analysis emphasized effects on the KPNA2, GABRA2, and CACNA1C expression in the brain. Sleep medications use was epidemiologically related to psychiatric traits in FinnGen (OR [95% (CI)] = 3.86 [3.78 to 3.94], p < 2 × 10-16), and the association was accentuated by genetic correlation and MR; depression (rg = 0.55 (0.027), p = 2.86 × 10-89, p MR = 4.5 × 10-5), schizophrenia (rg = 0.25 (0.026), p = 2.52 × 10-21, p MR = 2 × 10-4), and anxiety (rg = 0.44 (0.047), p = 2.88 × 10-27, p MR = 8.6 × 10-12). CONCLUSIONS: These results demonstrate the genetics behind sleep problems and the association between sleep problems and psychiatric traits. Our results highlight the scientific basis for sleep management in treating the impact of psychiatric diseases.

Risk of cardiovascular comorbidities before and after the onset of rheumatic diseases.

OBJECTIVES: To elucidate the risk and temporal relationship of cardiovascular (CV) comorbidities in rheumatic diseases. METHODS: Patients in the FinnGen study diagnosed between 2000 and 2014 with seropositive (n = 2368) or seronegative (n = 916) rheumatoid arthritis (RA), ankylosing spondylitis (AS, n = 715), psoriatic arthritis (PsA, n = 923), systemic lupus erythematosus (SLE, n = 190), primary Sjogren's syndrome (pSS, n = 412) or gout (n = 2034) were identified from healthcare registries. Each patient was matched based on age, sex, and birth region with twenty controls without any rheumatic conditions. Overall risk ratios (RR) were calculated by comparing the prevalence of seven CV diseases between patients and controls. Logistic regression models were used for estimating odds ratios (OR) for CV comorbidities before and after the onset of rheumatic diseases. RESULTS: The RR for 'any CVD' varied from 1.14 (95 % confidence interval [CI] 1.02-1.26) in PsA to 2.05 (95 % CI 1.67-2.52) in SLE. Patients with SLE or gout demonstrated over two-fold risks for several CV comorbidities. Among CV comorbidities, venous thromboembolism (VTE) showed the highest effect sizes in several rheumatic diseases. The ORs for CV comorbidities were highest within one year before and/or after the onset of the rheumatic disease. However, in gout the excess risk of CV disease was especially high before gout diagnosis. CONCLUSIONS: The risk of CV comorbidities was elevated in all studied rheumatic diseases, with highest risks observed in SLE and gout. The risk for CV diseases was highest immediately before and/or after rheumatic disease diagnosis, highlighting the increased risk for CV comorbidities across all rheumatic diseases very early on the disease course.

Comprehensive Inherited Risk Estimation for Risk-Based Breast Cancer Screening in Women.

PURPOSE: Family history (FH) and pathogenic variants (PVs) are used for guiding risk surveillance in selected high-risk women but little is known about their impact for breast cancer screening on population level. In addition, polygenic risk scores (PRSs) have been shown to efficiently stratify breast cancer risk through combining information about common genetic factors into one measure. METHODS: In longitudinal real-life data, we evaluate PRS, FH, and PVs for stratified screening. Using FinnGen (N = 117,252), linked to the Mass Screening Registry for breast cancer (1992-2019; nationwide organized biennial screening for age 50-69 years), we assessed the screening performance of a breast cancer PRS and compared its performance with FH of breast cancer and PVs in moderate- (CHEK2)- to high-risk (PALB2) susceptibility genes. RESULTS: Effect sizes for FH, PVs, and high PRS (>90th percentile) were comparable in screening-aged women, with similar implications for shifting age at screening onset. A high PRS identified women more likely to be diagnosed with breast cancer after a positive screening finding (positive predictive value [PPV], 39.5% [95% CI, 37.6 to 41.5]). Combinations of risk factors increased the PPVs up to 45% to 50%. A high PRS conferred an elevated risk of interval breast cancer (hazard ratio [HR], 2.78 [95% CI, 2.00 to 3.86] at age 50 years; HR, 2.48 [95% CI, 1.67 to 3.70] at age 60 years), and women with a low PRS (<10th percentile) had a low risk for both interval- and screen-detected breast cancers. CONCLUSION: Using real-life screening data, this study demonstrates the effectiveness of a breast cancer PRS for risk stratification, alone and combined with FH and PVs. Further research is required to evaluate their impact in a prospective risk-stratified screening program, including cost-effectiveness.

An immunogenetic basis for lung cancer risk.

Cancer risk is influenced by inherited mutations, DNA replication errors, and environmental factors. However, the influence of genetic variation in immunosurveillance on cancer risk is not well understood. Leveraging population-level data from the UK Biobank and FinnGen, we show that heterozygosity at the human leukocyte antigen (HLA)-II loci is associated with reduced lung cancer risk in smokers. Fine-mapping implicated amino acid heterozygosity in the HLA-II peptide binding groove in reduced lung cancer risk, and single-cell analyses showed that smoking drives enrichment of proinflammatory lung macrophages and HLA-II+ epithelial cells. In lung cancer, widespread loss of HLA-II heterozygosity (LOH) favored loss of alleles with larger neopeptide repertoires. Thus, our findings nominate genetic variation in immunosurveillance as a critical risk factor for lung cancer.

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.

Integration of Biomarker Polygenic Risk Score Improves Prediction of Coronary Heart Disease.

There are several established biomarkers for coronary heart disease (CHD), including blood pressure, cholesterol, and lipoproteins. It is of high interest to determine how a combined polygenic risk score (PRS) of CHD-associated biomarkers (BioPRS) can further improve genetic prediction of CHD. We developed CHDBioPRS, combining BioPRS with PRS of CHD in the UK Biobank and tested it on FinnGen. We found that BioPRS was clearly predictive of CHD and that CHDBioPRS improved the standard CHD PRS. The largest effect was observed with early onset cases in FinnGen, with HRs above 2 per standard deviation of CHDBioPRS.

Residual insulin secretion in individuals with type 1 diabetes in Finland: longitudinal and cross-sectional analyses.

BACKGROUND: Contrary to the presumption that type 1 diabetes leads to an absolute insulin deficiency, many individuals with type 1 diabetes have circulating C-peptide years after the diagnosis. We studied factors affecting random serum C-peptide concentration in individuals with type 1 diabetes and the association with diabetic complications. METHODS: Our longitudinal analysis included individuals newly diagnosed with type 1 diabetes from Helsinki University Hospital (Helsinki, Finland) with repeated random serum C-peptide and concomitant glucose measurements from within 3 months of diagnosis and at least once later. The long-term cross-sectional analysis included data from participants from 57 centres in Finland who had type 1 diabetes diagnosed after 5 years of age, initiation of insulin treatment within 1 year from diagnosis, and a C-peptide concentration of less than 1·0 nmol/L (FinnDiane study) and patients with type 1 diabetes from the DIREVA study. We tested the association of random serum C-peptide concentrations and polygenic risk scores with one-way ANOVA, and association of random serum C-peptide concentrations, polygenic risk scores, and clinical factors with logistic regression. FINDINGS: The longitudinal analysis included 847 participants younger than 16 years and 110 aged 16 years or older. In the longitudinal analysis, age at diagnosis strongly correlated with the decline in C-peptide secretion. The cross-sectional analysis included 3984 participants from FinnDiane and 645 from DIREVA. In the cross-sectional analysis, at a median duration of 21·6 years (IQR 12·5-31·2), 776 (19·4%) of 3984 FinnDiane participants had residual random serum C-peptide secretion (>0·02 nmol/L), which was associated with lower type 1 diabetes polygenic risk compared with participants without random serum C-peptide (p<0·0001). Random serum C-peptide was inversely associated with hypertension, HbA1c, and cholesterol, but also independently with microvascular complications (adjusted OR 0·61 [95% CI 0·38-0·96], p=0·033, for nephropathy; 0·55 [0·34-0·89], p=0·014, for retinopathy). INTERPRETATION: Although children with multiple autoantibodies and HLA risk genotypes progressed to absolute insulin deficiency rapidly, many adolescents and adults had residual random serum C-peptide decades after the diagnosis. Polygenic risk of type 1 and type 2 diabetes affected residual random serum C-peptide. Even low residual random serum C-peptide concentrations seemed to be associated with a beneficial complications profile. FUNDING: Folkhälsan Research Foundation; Academy of Finland; University of Helsinki and Helsinki University Hospital; Medical Society of Finland; the Sigrid Juselius Foundation; the "Liv and Hälsa" Society; Novo Nordisk Foundation; and State Research Funding via the Helsinki University Hospital, the Vasa Hospital District, Turku University Hospital, Vasa Central Hospital, Jakobstadsnejdens Heart Foundation, and the Medical Foundation of Vaasa.