Glycosylated haemoglobin: a false sense of security

E, Finan; Joseph, Joe

doi:10.1136/bcr-2018-227668

Cited by 4 publications

(3 citation statements)

References 20 publications

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“…One of these variants, 16:88719665:G:A or T2127M (rs587776991) is a gain of function variant that slows down inactivation kinetics of PIEZO1 in patients with dehydrated hereditary stomatocytosis (a disorder of red blood cells), together with other gain of function variants 39 – 41 . Decreased levels of HbA1c had previously been observed in individuals with red blood cell disorders 42 – 44 .…”

Section: Resultsmentioning

confidence: 70%

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

et al. 2022

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Here we present an exome-wide rare genetic variant association study for 30 blood biomarkers in 191,971 individuals in the UK Biobank. We compare gene-based association tests for separate functional variant categories to increase interpretability and identify 193 significant gene-biomarker associations. Genes associated with biomarkers were ~ 4.5-fold enriched for conferring Mendelian disorders. In addition to performing weighted gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for missense variants, splicing and the binding of RNA-binding proteins. For these tests, we present a computationally efficient combination of the likelihood-ratio and score tests that found 36% more associations than the score test alone while also controlling the type-1 error. Kernel-based tests identified 13% more associations than their gene-based collapsing counterparts and had advantages in the presence of gain of function missense variants. We introduce local collapsing by amino acid position for missense variants and use it to interpret associations and identify potential novel gain of function variants in PIEZO1. Our results show the benefits of investigating different functional mechanisms when performing rare-variant association tests, and demonstrate pervasive rare-variant contribution to biomarker variability.

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Section: Resultsmentioning

confidence: 70%

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

et al. 2022

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show abstract

“…One of these variants, 16:88719665:G:A or T2127M (rs587776991) is a gain of function variant that slows down inactivation kinetics of PIEZO1 in patients with dehydrated hereditary stomatocytosis (a disorder of red blood cells), together with other gain of function variants [39, 40]. Decreased levels of HbA1c had previously been observed in individuals with red blood cell disorders [41, 42, 43].…”

Section: Resultsmentioning

confidence: 99%

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

Monti

Rautenstrauch

et al. 2021

Preprint

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Here we present an exome-wide rare genetic variant association study for 30 biomarkers in 191,640 individuals in the UK Biobank. We perform gene-based association tests for separate functional variant categories to increase interpretability and identify 201 significant gene-biomarker associations, which include novel associations such as GIGYF1 with diabetes markers. In addition to performing gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for missense variants, splicing and the binding of RNA-binding proteins. For these tests we present a powerful and computationally efficient combination of the likelihood-ratio and score tests that found 32% more associations than the score test alone. Kernel-based tests identified 12-31% more associations than their gene-based collapsing counterparts with large overlaps, and had advantages in the presence of gain of function missense variants. We introduce local collapsing by amino acid position for missense variants and use this approach to identify potential novel gain of function variants in PIEZO1, and interpret a position-specific association of ABCA1-variants with inflammation marker CRP. Our results show the benefits of separately investigating different functional mechanisms when performing rare-variant association tests, and highlight the strengths of biomarker panels for large biobanks.

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“…Glycosylated haemoglobin (HbA1c) is used for the screening, diagnosis and the monitoring of diabetes mellitus. Values represent glycaemic control over the preceding 2–3 months and correlate with the development of diabetic complications 1 2. The turnover of HbA1c is dependent on the lifespan of red blood cells (90–120 days) and correlates with the glucose exposure of blood over that period 3…”

Section: Introductionmentioning

confidence: 99%

Falsely low glycosylated haemoglobin levels probably secondary to hypersplenism in a patient with diabetes mellitus

Hayakawa,

Leibowitz,

Nagumantry

et al. 2024

BMJ Case Rep

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A man in his 70s presented with a history of low glycated haemoglobin (HbA1c) values despite a diagnosis of type 2 diabetes. His blood glucose readings ranged between 8 and 15 mmol/L, but his HbA1c values were below 27 mmol/mol. Initial investigations demonstrated evidence of reduced red blood cell lifespan as a cause of misleadingly low HbA1c values. Further investigation revealed chronic liver disease and splenomegaly, with hypersplenism being the probable cause of increased red blood cell turnover. HbA1c estimation was no longer reliable, so ongoing diabetic care was guided by home capillary blood glucose monitoring. Healthcare providers and clinical laboratorians need to be aware of the possible clinical implications of very low HbA1c values in patients with type 2 diabetes.

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Glycosylated haemoglobin: a false sense of security

Cited by 4 publications

References 20 publications

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

Falsely low glycosylated haemoglobin levels probably secondary to hypersplenism in a patient with diabetes mellitus

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