The causal effects of lipid traits on kidney function in Africans: bidirectional and multivariable Mendelian-randomization study

Kintu, Christopher; Soremekun, Opeyemi; Kamiza, Abram Bunya; Kalungi, Allan; Mayanja, Richard; Kalyesubula, Robert; S, Bernard Bagaya; Jjingo, Daudi; Fabian, June; Nyirenda, Moffat; Nitsch, Dorothea; Chikowore, Tinashe; Fatumo, Segun

doi:10.1016/j.ebiom.2023.104537

Cited by 19 publications

(9 citation statements)

References 45 publications

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“…Sigfrids' research exhibited that remnant cholesterol concentration was indicative of both diabetic neuropathy progression and severe diabetic retinopathy (7). Kintu et al found that there appears to be a causal link between genetically higher LDL-C and TC levels and elevated eGFR levels (22). A study found that elevated blood TG levels might be linked in a causal manner to an increased risk of CKD (23).…”

Section: Discussionmentioning

confidence: 99%

The causal relationship between 5 serum lipid parameters and diabetic nephropathy: a Mendelian randomization study

Liu,

Yao,

Wang

et al. 2024

Front. Endocrinol.

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BackgroundSerum lipids were found to be correlated with chronic kidney disease and cardiovascular disease. Here, we aimed to research the potential causal associations between five serum lipid parameters and the risk of diabetic nephropathy using several Mendelian Randomization methods.MethodsGenetic data was obtained from the UK Biobank datasets. Causal effects were estimated using multiple MR methods. Heterogeneity and pleiotropy tests were performed.ResultsMR analysis revealed that HDL-C and TG exhibited causal associations with diabetic nephropathy (P<0.05). Similar trends were not observed for other lipid parameters.ConclusionsOur research has suggested links between HDL-C, TG and diabetic nephropathy. The findings could contribute to further elucidation of the disease etiology.Strengths and limitations of this studyThis article only uses Mendel randomization method to analyze the relationship between blood lipids and diabetes nephropathy, which is more convincing when combined with population data.

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Section: Discussionmentioning

confidence: 99%

The causal relationship between 5 serum lipid parameters and diabetic nephropathy: a Mendelian randomization study

Liu,

Yao,

Wang

et al. 2024

Front. Endocrinol.

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“…Several studies have linked apolipoproteins (APOA1, APOB and APOL1) with CKD (51-53) and hypertension (54). Moreover, a Mendelian-randomization study identified a causal association between lipids (including low-density lipoprotein and triglycerides) and kidney function in individuals of African ancestry (55). It has been postulated that the association between apolipoproteins and kidney disease may be mediated by the impact of these lipoprotein particles on the kidney.…”

Section: Discussionmentioning

confidence: 99%

Proteomic insights into the pathophysiology of hypertension-associated albuminuria: Pilot study in a South African cohort

Govender,

Stoychev,

Brandenburg

et al. 2023

Preprint

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BackgroundHypertension is an important public health priority with a high prevalence in Africa. It is also an independent risk factor for kidney outcomes. We aimed to identify potential proteins and pathways involved in hypertension-associated albuminuria by assessing urinary proteomic profiles in black South African participants with combined hypertension and albuminuria compared to those who have neither condition.MethodsThe study included 24 South African cases with both hypertension and albuminuria and 49 control participants who had neither condition. Protein was extracted from urine samples and analysed using ultra-high-performance liquid chromatography coupled with mass spectrometry. Data was generated using data-independent acquisition (DIA) and processed using Spectronaut™ 15. Statistical and functional data annotation were performed on Perseus and Cytoscape to identify and annotate differentially abundant proteins. Machine learning was applied to the dataset using the OmicLearn platform.ResultsOverall, a mean of 1,225 and 915 proteins were quantified in the control and case groups, respectively. Three hundred and thirty-two differentially abundant proteins were constructed into a network. Pathways associated with these differentially abundant proteins included the immune system (q-value [false discovery rate]=1.4×10-45), innate immune system (q=1.1×10-32), extracellular matrix (ECM) organisation (q=0.03) and activation of matrix metalloproteinases (q=0.04). Proteins with high disease scores (76–100% confidence) for both hypertension and CKD included angiotensinogen (AGT), albumin (ALB), apolipoprotein L1 (APOL1), and uromodulin (UMOD). A machine learning approach was able to identify a set of 20 proteins, differentiating between cases and controls.ConclusionsThe urinary proteomic data combined with the machine learning approach was able to classify disease status and identify proteins and pathways associated with hypertension and albuminuria.

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“…Furthermore, to assess the strength of the screened IVs, this study introduced the F statistic to reflect the ability of the IVs to represent the phenotype. The F statistic was calculated from the sample size, the number of IVs, the minor allele frequency (MAF), and the β-value ( 26 ). IVs with F-statistics <10 were regarded as weak genetic instruments.…”

Section: Methodsmentioning

confidence: 99%

Genetically predicted lipids mediate the association between intrahepatic cholestasis of pregnancy and cardiovascular disease

Cui,

Zhai,

Chen

et al. 2024

Front. Cardiovasc. Med.

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IntroductionIntrahepatic cholestasis of pregnancy (ICP), the most prevalent liver disorder specific to pregnancy, affects approximately 1.5%-4% of pregnancies. However, the influence of ICP on cardiovascular disease (CVD), including hypertension (HTN) and coronary artery disease (CAD), has not been thoroughly investigated.MethodsThis study explores the causal relationship between ICP and CVD (HTN, CAD) using Mendelian Randomization (MR). Utilizing summary-level data from Genome-Wide Association Studies (GWAS), we applied the inverse-variance weighted (IVW) method, supplemented by sensitivity and reverse MR analyses, to ascertain robustness.ResultsOur findings reveal significant causal links, indicating ICP notably increases the risk of CVD (P = 0.001), hypertension (HTN, P = 0.024), and coronary artery disease (CAD, P = 0.039). A two-step MR analysis highlighted the mediation role of lipid profiles, with LDL, TC, and Apo-B contributing to increased CVD risk by 25.5%, 12.2%, and 21.3%, respectively. Additionally, HTN was identified as a mediator in the ICP-CAD association, accounting for a 14.5% mediation effect.DiscussionThe results underscore the genetic predisposition of ICP to elevate CVD risk and the critical mediating role of lipid levels, emphasizing the need for vigilant lipid monitoring and early intervention in individuals with ICP.

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The causal effects of lipid traits on kidney function in Africans: bidirectional and multivariable Mendelian-randomization study

Cited by 19 publications

References 45 publications

The causal relationship between 5 serum lipid parameters and diabetic nephropathy: a Mendelian randomization study

The causal relationship between 5 serum lipid parameters and diabetic nephropathy: a Mendelian randomization study

Proteomic insights into the pathophysiology of hypertension-associated albuminuria: Pilot study in a South African cohort

Genetically predicted lipids mediate the association between intrahepatic cholestasis of pregnancy and cardiovascular disease

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