The Impact of the International Cooperation On Familial Hypercholesterolemia Screening and Treatment: results from the ScreenPro FH Project

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Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

Background: Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life

A Combination of CD28 (rs1980422) and IRF5 (rs10488631) Polymorphisms Is Associated with Seropositivity in Rheumatoid Arthritis: A Case Control Study.

INTRODUCTION:The aim of the study was to analyse genetic architecture of RA by utilizing multiparametric statistical methods such as linear discriminant analysis (LDA) and redundancy analysis (RDA). METHODS:A total of 1393 volunteers, 499 patients with RA and 894 healthy controls were included in the study. The presence of shared epitope (SE) in HLA-DRB1 and 11 SNPs (PTPN22 C/T (rs2476601), STAT4 G/T (rs7574865), CTLA4 A/G (rs3087243), TRAF1/C5 A/G (rs3761847), IRF5 T/C (rs10488631), TNFAIP3 C/T (rs5029937), AFF3 A/T (rs11676922), PADI4 C/T (rs2240340), CD28 T/C (rs1980422), CSK G/A (rs34933034) and FCGR3A A/C (rs396991), rheumatoid factor (RF), anti-citrullinated protein antibodies (ACPA) and clinical status was analysed using the LDA and RDA. RESULTS:HLA-DRB1, PTPN22, STAT4, IRF5 and PADI4 significantly discriminated between RA patients and healthy controls in LDA. The correlation between RA diagnosis and the explanatory variables in the model was 0.328 (Trace = 0.107; F = 13.715; P = 0.0002). The risk variants of IRF5 and CD28 genes were found to be common determinants for seropositivity in RDA, while positivity of RF alone was associated with the CTLA4 risk variant in heterozygous form. The correlation between serologic status and genetic determinants on the 1st ordinal axis was 0.468, and 0.145 on the 2nd one (Trace = 0.179; F = 6.135; P = 0.001). The risk alleles in AFF3 gene together with the presence of ACPA were associated with higher clinical severity of RA. CONCLUSIONS:The association among multiple risk variants related to T cell receptor signalling with seropositivity may play an important role in distinct clinical phenotypes of RA. Our study demonstrates that multiparametric analyses represent a powerful tool for investigation of mutual relationships of potential risk factors in complex diseases such as RA

Factors associated with clinical severity in RA.

<p>Redundancy analysis plot showing that risk alleles in AFF3 gene, together with ACPA positivity are associated with higher clinical severity of RA. ACPA—anti-citrullinated peptides antibodies (□); <i>AFF3</i> (TT, AT, AA)–genotypes in <i>AFF3</i> gene (T risk allele) (▽). Diagram reading clue: Symbols are genetic and serologic factors. Large bold symbols represent genotypes and antibody presence significantly influencing the clinical parameters of disease severity (DAS28, CRP, ESR, TJC, SJC, HAQ-DI). Small empty symbols represent other factors and genotypes of selected genes. Direction of arrow indicates which of the clinical factors are associated with the genetic and serologic parameters and the length of the arrow indicates the magnitude of the association.</p

SNPs associated with seropositivity in RA.

<p>Redundancy discrimination analysis plot showing that IRF5, CD28 and CTLA4 are associated with seropositivity in RA patients. RF+–rheumatoid factor positive RA patients; RF-–rheumatoid factor negative RA patients; ACPA+–anti-citrullinated peptides antibodies positive RA patients; ACPA-–anti-citrullinated peptides antibodies negative RA patients; SE (0,1,2)—number of shared epitope coding alleles in HLA-DRB1 gene (✧); IRF5 (CC, CT, TT)—genotypes in IRF5 gene (C risk allele) (▷); CD28 (CC, CT, TT)–genotypes in CD28 gene (C risk allele) (◁); CTLA4 (AG, GG, AA)–genotypes in CTLA4 gene (G risk allele) (◊). Diagram reading clue: Symbols are genetic factors. Large bold symbols represent genotypes significantly influencing the presence of RF and ACPA. Small empty symbols represent other genotypes of selected genes. Direction of arrow indicates which serologic status is associated with the genetic parameters and the length of the arrow indicates the magnitude of the association.</p

The genetic discrimination of RA patients and controls.

<p>Linear discrimination analysis diagram shows that shared epitope and single nucleotide polymorphisms in PTPN22, STAT4, IRF5 and PADI4 genes significantly discriminated between RA patients and healthy controls. RA—RA patients; C—control group; SE (0,1,2)—number of SE coding allele in HLA-DRB1 gene (✧); IRF5 (CC, CT, TT)—genotypes in IRF5 gene (C risk allele) (◁); PADI4 (TT, CT, CC)–genotypes in PADI4 gene (T risk allele) (▽); PTPN22 (CC, CT, TT)–genotypes in PTPN22 gene (A risk allele) (△); STAT4 (GG, GT, TT)–genotypes in STAT4 gene (T risk allele) (☐). Diagram reading clue: Small circles represent individual cases. Large grey circles—centroids—represent subject groups (RA patients and controls). Symbols are genetic factors. Large bold symbols represent genotypes significantly influencing the distribution of subjects. Small empty symbols represent other genotypes of selected genes. The closer to the group centroid the gene symbol lies, the stronger is its impact on the classification of subjects to particular group.</p

Basic demographics of RA cases and healthy controls.

<p>Basic demographics of RA cases and healthy controls.</p

Moderate Alcohol Consumption Is Associated With Lower Risk for Heart Failure But Not Atrial Fibrillation

Objectives The aim of this study was to assess the hypothesis that alcohol consumption is associated with onset of atrial fibrillation (AF) and/or heart failure (HF). Background The connection between ethanol intake and AF or HF remains controversial. Methods The study population was 22,824 AF- or HF-free subjects (48% men, age \ue2\u89\ua535 years) randomly recruited from the general population included in the Moli-sani study, for whom complete data on HF, AF, and alcohol consumption were available. The cohort was followed up to December 31, 2015, for a median of 8.2 years (183,912 person-years). Incident cases were identified through linkage to the Molise regional archive of hospital discharges. Hazard ratios were calculated using Cox proportional hazard models and cubic spline regression. Results A total of 943 incident cases of HF and 554 of AF were identified. In comparison with never drinkers, both former and occasional drinkers showed comparable risk for developing HF. Drinking alcohol in the range of 1 to 4 drinks/day was associated with a lower risk for HF, with a 22% maximum risk reduction at 20 g/day, independent of common confounders. In contrast, no association of alcohol consumption with onset of AF was observed. Very similar results were obtained after restriction of the analyses to regular or only wine drinkers or according to sex, age, social status, or adherence to the Mediterranean diet. Conclusions Consumption of alcohol in moderation was associated with a lower incidence of HF but not with development of AF