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1.
Am J Hum Genet ; 2019 Oct 30.
Artigo em Inglês | MEDLINE | ID: mdl-31679650

RESUMO

Cytokines are essential regulatory components of the immune system, and their aberrant levels have been linked to many disease states. Despite increasing evidence that cytokines operate in concert, many of the physiological interactions between cytokines, and the shared genetic architecture that underlies them, remain unknown. Here, we aimed to identify and characterize genetic variants with pleiotropic effects on cytokines. Using three population-based cohorts (n = 9,263), we performed multivariate genome-wide association studies (GWAS) for a correlation network of 11 circulating cytokines, then combined our results in meta-analysis. We identified a total of eight loci significantly associated with the cytokine network, of which two (PDGFRB and ABO) had not been detected previously. In addition, conditional analyses revealed a further four secondary signals at three known cytokine loci. Integration, through the use of Bayesian colocalization analysis, of publicly available GWAS summary statistics with the cytokine network associations revealed shared causal variants between the eight cytokine loci and other traits; in particular, cytokine network variants at the ABO, SERPINE2, and ZFPM2 loci showed pleiotropic effects on the production of immune-related proteins, on metabolic traits such as lipoprotein and lipid levels, on blood-cell-related traits such as platelet count, and on disease traits such as coronary artery disease and type 2 diabetes.

3.
Scand Cardiovasc J ; : 1-7, 2019 Nov 08.
Artigo em Inglês | MEDLINE | ID: mdl-31701776

RESUMO

Objectives. To examine the validity of ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) diagnoses in Finnish nation-wide hospital discharge register (HDR). Design. In the first stage of the study, we sampled 180 patients treated in 1996-2012 for MI in three different hospitals, Oulu university hospital, Turku university hospital and North Karelia Central hospital, 60 patients in each hospital. A cardiology resident classified the patients on the basis of ECG finding into following categories: NSTEMI, STEMI or not classifiable myocardial infarction (NCMI). In the second stage of the study, we sampled altogether 270 additional patients i.e. 90 patients per hospital. Patients were treated between 2012-2014 for STEMI (n = 3 × 30), NSTEMI (n = 3 × 30), and NCMI (n = 3 × 30). The ECGs of these patients were independently evaluated by the cardiology resident and a senior cardiologist and compared with the HDR diagnosis. Results. In the first stage of the study, the agreement between the ECG coding of the cardiology resident and the HDR diagnoses was poor (Cohen's kappa coefficient 0.38 (95% CI 0.10-0.32). In the second stage, the agreement remained at the same poor level (Cohen's kappa = 0.22 (95% CI 0.11-0.03)). The agreement between the cardiology resident and the senior cardiologist was, however, good (Cohen's kappa = 0.75 (95% CI 0.65-0.85)). Conclusions. Our results show that the division of MI diagnoses to STEMI and NSTEMI is not reliable in the Finnish HDR. These diagnoses should not be used as outcomes in scientific research without additional verification from the original ECGs.

4.
PLoS Biol ; 17(10): e3000443, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31626640

RESUMO

Obesity is associated with changes in the plasma lipids. Although simple lipid quantification is routinely used, plasma lipids are rarely investigated at the level of individual molecules. We aimed at predicting different measures of obesity based on the plasma lipidome in a large population cohort using advanced machine learning modeling. A total of 1,061 participants of the FINRISK 2012 population cohort were randomly chosen, and the levels of 183 plasma lipid species were measured in a novel mass spectrometric shotgun approach. Multiple machine intelligence models were trained to predict obesity estimates, i.e., body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), and body fat percentage (BFP), and validated in 250 randomly chosen participants of the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC). Comparison of the different models revealed that the lipidome predicted BFP the best (R2 = 0.73), based on a Lasso model. In this model, the strongest positive and the strongest negative predictor were sphingomyelin molecules, which differ by only 1 double bond, implying the involvement of an unknown desaturase in obesity-related aberrations of lipid metabolism. Moreover, we used this regression to probe the clinically relevant information contained in the plasma lipidome and found that the plasma lipidome also contains information about body fat distribution, because WHR (R2 = 0.65) was predicted more accurately than BMI (R2 = 0.47). These modeling results required full resolution of the lipidome to lipid species level, and the predicting set of biomarkers had to be sufficiently large. The power of the lipidomics association was demonstrated by the finding that the addition of routine clinical laboratory variables, e.g., high-density lipoprotein (HDL)- or low-density lipoprotein (LDL)- cholesterol did not improve the model further. Correlation analyses of the individual lipid species, controlled for age and separated by sex, underscores the multiparametric and lipid species-specific nature of the correlation with the BFP. Lipidomic measurements in combination with machine intelligence modeling contain rich information about body fat amount and distribution beyond traditional clinical assays.

5.
PLoS One ; 14(10): e0223692, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31644575

RESUMO

BACKGROUND: GlycA is a nuclear magnetic resonance (NMR) spectroscopy biomarker that predicts risk of disease from myriad causes. It is heterogeneous; arising from five circulating glycoproteins with dynamic concentrations: alpha-1 antitrypsin (AAT), alpha-1-acid glycoprotein (AGP), haptoglobin (HP), transferrin (TF), and alpha-1-antichymotrypsin (AACT). The contributions of each glycoprotein to the disease and mortality risks predicted by GlycA remain unknown. METHODS: We trained imputation models for AAT, AGP, HP, and TF from NMR metabolite measurements in 626 adults from a population cohort with matched NMR and immunoassay data. Levels of AAT, AGP, and HP were estimated in 11,861 adults from two population cohorts with eight years of follow-up, then each biomarker was tested for association with all common endpoints. Whole blood gene expression data was used to identify cellular processes associated with elevated AAT. RESULTS: Accurate imputation models were obtained for AAT, AGP, and HP but not for TF. While AGP had the strongest correlation with GlycA, our analysis revealed variation in imputed AAT levels was the most predictive of morbidity and mortality for the widest range of diseases over the eight year follow-up period, including heart failure (meta-analysis hazard ratio = 1.60 per standard deviation increase of AAT, P-value = 1×10-10), influenza and pneumonia (HR = 1.37, P = 6×10-10), and liver diseases (HR = 1.81, P = 1×10-6). Transcriptional analyses revealed association of elevated AAT with diverse inflammatory immune pathways. CONCLUSIONS: This study clarifies the molecular underpinnings of the GlycA biomarker's associated disease risk, and indicates a previously unrecognised association between elevated AAT and severe disease onset and mortality.

7.
Diabetologia ; 2019 Oct 04.
Artigo em Inglês | MEDLINE | ID: mdl-31584131

RESUMO

AIMS/HYPOTHESIS: Metabolomics technologies have identified numerous blood biomarkers for type 2 diabetes risk in case-control studies of middle-aged and older individuals. We aimed to validate existing and identify novel metabolic biomarkers predictive of future diabetes in large cohorts of young adults. METHODS: NMR metabolomics was used to quantify 229 circulating metabolic measures in 11,896 individuals from four Finnish observational cohorts (baseline age 24-45 years). Associations between baseline metabolites and risk of developing diabetes during 8-15 years of follow-up (392 incident cases) were adjusted for sex, age, BMI and fasting glucose. Prospective metabolite associations were also tested with fasting glucose, 2 h glucose and HOMA-IR at follow-up. RESULTS: Out of 229 metabolic measures, 113 were associated with incident type 2 diabetes in meta-analysis of the four cohorts (ORs per 1 SD: 0.59-1.50; p< 0.0009). Among the strongest biomarkers of diabetes risk were branched-chain and aromatic amino acids (OR 1.31-1.33) and triacylglycerol within VLDL particles (OR 1.33-1.50), as well as linoleic n-6 fatty acid (OR 0.75) and non-esterified cholesterol in large HDL particles (OR 0.59). The metabolic biomarkers were more strongly associated with deterioration in post-load glucose and insulin resistance than with future fasting hyperglycaemia. A multi-metabolite score comprised of phenylalanine, non-esterified cholesterol in large HDL and the ratio of cholesteryl ester to total lipid in large VLDL was associated with future diabetes risk (OR 10.1 comparing individuals in upper vs lower fifth of the multi-metabolite score) in one of the cohorts (mean age 31 years). CONCLUSIONS/INTERPRETATION: Metabolic biomarkers across multiple molecular pathways are already predictive of the long-term risk of diabetes in young adults. Comprehensive metabolic profiling may help to target preventive interventions for young asymptomatic individuals at increased risk.

8.
Nat Commun ; 10(1): 4329, 2019 Sep 24.
Artigo em Inglês | MEDLINE | ID: mdl-31551469

RESUMO

Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10-8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.

9.
Nature ; 572(7769): 323-328, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31367044

RESUMO

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power.

10.
J Am Heart Assoc ; 8(13): e012415, 2019 Jul 02.
Artigo em Inglês | MEDLINE | ID: mdl-31256696

RESUMO

Background We asked whether, after excluding familial hypercholesterolemia, individuals with high low-density lipoprotein cholesterol ( LDL -C) or triacylglyceride levels and a family history of the same hyperlipidemia have greater coronary artery disease risk or different lipidomic profiles compared with population-based hyperlipidemias. Methods and Results We determined incident coronary artery disease risk for 755 members of 66 hyperlipidemic families (≥2 first-degree relatives with similar hyperlipidemia) and 19 644 Finnish FINRISK population study participants. We quantified 151 circulating lipid species from 550 members of 73 hyperlipidemic families and 897 FINRISK participants using mass spectrometric shotgun lipidomics. Familial hypercholesterolemia was excluded using functional LDL receptor testing and genotyping. Hyperlipidemias ( LDL -C or triacylglycerides >90th population percentile) associated with increased coronary artery disease risk in meta-analysis of the hyperlipidemic families and the population cohort (high LDL -C: hazard ratio, 1.74 [95% CI, 1.48-2.04]; high triacylglycerides: hazard ratio, 1.38 [95% CI, 1.09-1.74]). Risk estimates were similar in the family and population cohorts also after adjusting for lipid-lowering medication. In lipidomic profiling, high LDL -C associated with 108 lipid species, and high triacylglycerides associated with 131 lipid species in either cohort (at 5% false discovery rate; P-value range 0.038-2.3×10-56). Lipidomic profiles were highly similar for hyperlipidemic individuals in the families and the population ( LDL -C: r=0.80; triacylglycerides: r=0.96; no lipid species deviated between the cohorts). Conclusions Hyperlipidemias with family history conferred similar coronary artery disease risk as population-based hyperlipidemias. We identified distinct lipidomic profiles associated with high LDL -C and triacylglycerides. Lipidomic profiles were similar between hyperlipidemias with family history and population-ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms.

11.
Am J Hum Genet ; 104(6): 1169-1181, 2019 Jun 06.
Artigo em Inglês | MEDLINE | ID: mdl-31155286

RESUMO

Polygenic scores (PSs) are becoming a useful tool to identify individuals with high genetic risk for complex diseases, and several projects are currently testing their utility for translational applications. It is also tempting to use PSs to assess whether genetic variation can explain a part of the geographic distribution of a phenotype. However, it is not well known how the population genetic properties of the training and target samples affect the geographic distribution of PSs. Here, we evaluate geographic differences, and related biases, of PSs in Finland in a geographically well-defined sample of 2,376 individuals from the National FINRISK study. First, we detect geographic differences in PSs for coronary artery disease (CAD), rheumatoid arthritis, schizophrenia, waist-hip ratio (WHR), body-mass index (BMI), and height, but not for Crohn disease or ulcerative colitis. Second, we use height as a model trait to thoroughly assess the possible population genetic biases in PSs and apply similar approaches to the other phenotypes. Most importantly, we detect suspiciously large accumulations of geographic differences for CAD, WHR, BMI, and height, suggesting bias arising from the population's genetic structure rather than from a direct genotype-phenotype association. This work demonstrates how sensitive the geographic patterns of current PSs are for small biases even within relatively homogeneous populations and provides simple tools to identify such biases. A thorough understanding of the effects of population genetic structure on PSs is essential for translational applications of PSs.

13.
Scand J Public Health ; : 1403494819847051, 2019 May 09.
Artigo em Inglês | MEDLINE | ID: mdl-31068116

RESUMO

BACKGROUND: Contemporary validation studies of register-based heart failure diagnoses based on current guidelines and complete clinical data are lacking in Finland and internationally. Our objective was to assess the positive and negative predictive values of heart failure diagnoses in a nationwide hospital discharge register. METHODS: Using Finnish Hospital Discharge Register data from 2013-2015, we obtained the medical records for 120 patients with a register-based diagnosis for heart failure (cases) and for 120 patients with a predisposing condition for heart failure, but without a heart failure diagnosis (controls). The medical records of all patients were assessed by a physician who categorized each individual as having heart failure (with reduced or preserved ejection fraction) or no heart failure, based on the definition of current European Society of Cardiology heart failure guidelines. Unclear cases were assessed by a panel of three physicians. This classification was considered as the clinical gold standard, against which the registers were assessed. RESULTS: Register-based heart failure diagnoses had a positive predictive value of 0.85 (95% CI 0.77-0.91) and a negative predictive value of 0.83 (95% CI 0.75-0.90). The positive predictive value decreased when we classified patients with transient heart failure (duration <6 months), dialysis/lung disease or heart failure with preserved ejection fraction as not having heart failure. CONCLUSIONS: Heart failure diagnoses of the Finnish Hospital Discharge Register have good positive predictive value and negative predictive value, even when patients with pre-existing heart conditions are used as healthy controls. Our results suggest that heart failure diagnoses based on register data can be reliably used for research purposes.

14.
Nat Commun ; 10(1): 410, 2019 01 24.
Artigo em Inglês | MEDLINE | ID: mdl-30679432

RESUMO

The contribution of de novo variants in severe intellectual disability (ID) has been extensively studied whereas the genetics of mild ID has been less characterized. To elucidate the genetics of milder ID we studied 442 ID patients enriched for mild ID (>50%) from a population isolate of Finland. Using exome sequencing, we show that rare damaging variants in known ID genes are observed significantly more often in severe (27%) than in mild ID (13%) patients. We further observe a significant enrichment of functional variants in genes not yet associated with ID (OR: 2.1). We show that a common variant polygenic risk significantly contributes to ID. The heritability explained by polygenic risk score is the highest for educational attainment (EDU) in mild ID (2.2%) but lower for more severe ID (0.6%). Finally, we identify a Finland enriched homozygote variant in the CRADD ID associated gene.


Assuntos
Variações do Número de Cópias de DNA/genética , Variação Genética/genética , Genoma Humano/genética , Deficiência Intelectual/epidemiologia , Deficiência Intelectual/genética , Proteína Adaptadora de Sinalização CRADD/genética , Disfunção Cognitiva/epidemiologia , Disfunção Cognitiva/genética , Estudos de Coortes , Exoma , Feminino , Finlândia/epidemiologia , Estudos de Associação Genética , Doenças Genéticas Inatas/epidemiologia , Doenças Genéticas Inatas/genética , Predisposição Genética para Doença , Geografia , Homozigoto , Humanos , Deficiência Intelectual/diagnóstico , Masculino , Herança Multifatorial , Mutação , Transtornos do Neurodesenvolvimento/epidemiologia , Transtornos do Neurodesenvolvimento/genética , Patologia Molecular , Prevalência , Sequenciamento Completo do Exoma
15.
Circ Genom Precis Med ; 11(11): e002234, 2018 11.
Artigo em Inglês | MEDLINE | ID: mdl-30571186

RESUMO

BACKGROUND: Integration of systems-level biomolecular information with electronic health records has led to recent interest in the glycoprotein acetyls (GlycA) biomarker-a serum- or plasma-derived nuclear magnetic resonance spectroscopy signal that represents the abundance of circulating glycated proteins. GlycA predicts risk of diverse outcomes, including cardiovascular disease, type 2 diabetes mellitus, and all-cause mortality; however, the underlying detailed associations of GlycA's morbidity and mortality risk are currently unknown. METHODS: We used 2 population-based cohorts totaling 11 861 adults from the Finnish general population to test for an association with 468 common incident hospitalization and mortality outcomes during an 8-year follow-up. Further, we utilized 900 angiography patients to test for GlycA association with mortality risk and potential utility for mortality risk discrimination during 12-year follow-up. RESULTS: New associations with GlycA and incident alcoholic liver disease, chronic renal failure, glomerular diseases, chronic obstructive pulmonary disease, inflammatory polyarthropathies, and hypertension were uncovered, and known incident disease associations were replicated. GlycA associations for incident disease outcomes were in general not attenuated when adjusting for hsCRP (high-sensitivity C-reactive protein). Among 900 patients referred to angiography, GlycA had hazard ratios of 4.87 (95% CI, 2.45-9.65) and 5.00 (95% CI, 2.38-10.48) for 12-year risk of mortality in the fourth and fifth quintiles by GlycA levels, demonstrating its prognostic potential for identification of high-risk individuals. When modeled together, both hsCRP and GlycA were attenuated but remained significant. CONCLUSIONS: GlycA was predictive of myriad incident diseases across many major internal organs and stratified mortality risk in angiography patients. Both GlycA and hsCRP had shared and independent contributions to mortality risk, suggesting chronic inflammation as an etiological factor. GlycA may be useful in improving risk prediction in specific disease settings.


Assuntos
Ciências Biocomportamentais , Doenças Cardiovasculares , Diabetes Mellitus Tipo 2 , Nefropatias , Angiografia por Ressonância Magnética , Adulto , Idoso , Biomarcadores/sangue , Doenças Cardiovasculares/sangue , Doenças Cardiovasculares/diagnóstico por imagem , Diabetes Mellitus Tipo 2/sangue , Diabetes Mellitus Tipo 2/diagnóstico por imagem , Intervalo Livre de Doença , Feminino , Humanos , Nefropatias/sangue , Nefropatias/diagnóstico por imagem , Masculino , Pessoa de Meia-Idade , Fatores de Risco , Taxa de Sobrevida
16.
BMJ Open ; 8(10): e022752, 2018 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-30327404

RESUMO

OBJECTIVE: To evaluate if obstructive sleep apnoea (OSA) modifies the risk of coronary heart disease, type 2 diabetes (T2D) and diabetic complications in a gender-specific fashion. DESIGN AND SETTING: A longitudinal population-based study with up to 25-year follow-up data on 36 963 individuals (>500 000 person years) from three population-based cohorts: the FINRISK study, the Health 2000 Cohort Study and the Botnia Study. MAIN OUTCOME MEASURES: Incident coronary heart disease, diabetic kidney disease, T2D and all-cause mortality from the Finnish National Hospital Discharge Register and the Finnish National Causes-of-Death Register. RESULTS: After adjustments for age, sex, region, high-density lipoprotein (HDL) and total cholesterol, current cigarette smoking, body mass index, hypertension, T2D baseline and family history of stroke or myocardial infarction, OSA increased the risk for coronary heart disease (HR=1.36, p=0.0014, 95% CI 1.12 to 1.64), particularly in women (HR=2.01, 95% CI 1.31 to 3.07, p=0.0012). T2D clustered with OSA independently of obesity (HR=1.48, 95% CI 1.26 to 1.73, p=9.11×[Formula: see text]). The risk of diabetic kidney disease increased 1.75-fold in patients with OSA (95% CI 1.13 to 2.71, p=0.013). OSA increased the risk for coronary heart disease similarly among patients with T2D and in general population (HR=1.36). All-cause mortality was increased by OSA in diabetic individuals (HR=1.35, 95% CI 1.06 to 1.71, p=0.016). CONCLUSION: OSA is an independent risk factor for coronary heart disease, T2D and diabetic kidney disease. This effect is more pronounced even in women, who until now have received less attention in diagnosis and treatment of OSA than men.

17.
Eur Heart J ; 39(44): 3961-3969, 2018 Nov 21.
Artigo em Inglês | MEDLINE | ID: mdl-30169657

RESUMO

Aims: Sudden cardiac arrest (SCA) accounts for 10% of adult mortality in Western populations. We aim to identify potential loci associated with SCA and to identify risk factors causally associated with SCA. Methods and results: We carried out a large genome-wide association study (GWAS) for SCA (n = 3939 cases, 25 989 non-cases) to examine common variation genome-wide and in candidate arrhythmia genes. We also exploited Mendelian randomization (MR) methods using cross-trait multi-variant genetic risk score associations (GRSA) to assess causal relationships of 18 risk factors with SCA. No variants were associated with SCA at genome-wide significance, nor were common variants in candidate arrhythmia genes associated with SCA at nominal significance. Using cross-trait GRSA, we established genetic correlation between SCA and (i) coronary artery disease (CAD) and traditional CAD risk factors (blood pressure, lipids, and diabetes), (ii) height and BMI, and (iii) electrical instability traits (QT and atrial fibrillation), suggesting aetiologic roles for these traits in SCA risk. Conclusions: Our findings show that a comprehensive approach to the genetic architecture of SCA can shed light on the determinants of a complex life-threatening condition with multiple influencing factors in the general population. The results of this genetic analysis, both positive and negative findings, have implications for evaluating the genetic architecture of patients with a family history of SCA, and for efforts to prevent SCA in high-risk populations and the general community.

18.
Mol Psychiatry ; 2018 Aug 14.
Artigo em Inglês | MEDLINE | ID: mdl-30108311

RESUMO

The Alzheimer's Disease Sequencing Project (ADSP) undertook whole exome sequencing in 5,740 late-onset Alzheimer disease (AD) cases and 5,096 cognitively normal controls primarily of European ancestry (EA), among whom 218 cases and 177 controls were Caribbean Hispanic (CH). An age-, sex- and APOE based risk score and family history were used to select cases most likely to harbor novel AD risk variants and controls least likely to develop AD by age 85 years. We tested ~1.5 million single nucleotide variants (SNVs) and 50,000 insertion-deletion polymorphisms (indels) for association to AD, using multiple models considering individual variants as well as gene-based tests aggregating rare, predicted functional, and loss of function variants. Sixteen single variants and 19 genes that met criteria for significant or suggestive associations after multiple-testing correction were evaluated for replication in four independent samples; three with whole exome sequencing (2,778 cases, 7,262 controls) and one with genome-wide genotyping imputed to the Haplotype Reference Consortium panel (9,343 cases, 11,527 controls). The top findings in the discovery sample were also followed-up in the ADSP whole-genome sequenced family-based dataset (197 members of 42 EA families and 501 members of 157 CH families). We identified novel and predicted functional genetic variants in genes previously associated with AD. We also detected associations in three novel genes: IGHG3 (p = 9.8 × 10-7), an immunoglobulin gene whose antibodies interact with ß-amyloid, a long non-coding RNA AC099552.4 (p = 1.2 × 10-7), and a zinc-finger protein ZNF655 (gene-based p = 5.0 × 10-6). The latter two suggest an important role for transcriptional regulation in AD pathogenesis.

19.
Am J Hum Genet ; 102(6): 1204-1211, 2018 06 07.
Artigo em Inglês | MEDLINE | ID: mdl-29861106

RESUMO

There is a limited understanding about the impact of rare protein-truncating variants across multiple phenotypes. We explore the impact of this class of variants on 13 quantitative traits and 10 diseases using whole-exome sequencing data from 100,296 individuals. Protein-truncating variants in genes intolerant to this class of mutations increased risk of autism, schizophrenia, bipolar disorder, intellectual disability, and ADHD. In individuals without these disorders, there was an association with shorter height, lower education, increased hospitalization, and reduced age at enrollment. Gene sets implicated from GWASs did not show a significant protein-truncating variants burden beyond what was captured by established Mendelian genes. In conclusion, we provide a thorough investigation of the impact of rare deleterious coding variants on complex traits, suggesting widespread pleiotropic risk.

20.
Am J Hum Genet ; 102(5): 760-775, 2018 05 03.
Artigo em Inglês | MEDLINE | ID: mdl-29706349

RESUMO

Finland provides unique opportunities to investigate population and medical genomics because of its adoption of unified national electronic health records, detailed historical and birth records, and serial population bottlenecks. We assembled a comprehensive view of recent population history (≤100 generations), the timespan during which most rare-disease-causing alleles arose, by comparing pairwise haplotype sharing from 43,254 Finns to that of 16,060 Swedes, Estonians, Russians, and Hungarians from geographically and linguistically adjacent countries with different population histories. We find much more extensive sharing in Finns, with at least one ≥ 5 cM tract on average between pairs of unrelated individuals. By coupling haplotype sharing with fine-scale birth records from more than 25,000 individuals, we find that although haplotype sharing broadly decays with geographical distance, there are pockets of excess haplotype sharing; individuals from northeast Finland typically share several-fold more of their genome in identity-by-descent segments than individuals from southwest regions. We estimate recent effective population-size changes through time across regions of Finland, and we find that there was more continuous gene flow as Finns migrated from southwest to northeast between the early- and late-settlement regions than was dichotomously described previously. Lastly, we show that haplotype sharing is locally enriched by an order of magnitude among pairs of individuals sharing rare alleles and especially among pairs sharing rare disease-causing variants. Our work provides a general framework for using haplotype sharing to reconstruct an integrative view of recent population history and gain insight into the evolutionary origins of rare variants contributing to disease.

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