Implementation of a genomic healthcare strategy that incorporates the effect of moderate alcohol consumption on iron metabolism and inflammation

Project Number
N09 08-224 2014

Project title
Implementation of a genomic healthcare strategy that incorporates the effect of moderate alcohol consumption on iron metabolism and inflammation

Project leader
Kotze, M J

University of Stellenbosch. Faculty of Health Sciences. Department of Pathology

Team members
Kotze, M J
Van Velden, D P
Kidd, M
Fisher, L R
Moremi, L
Masconi, K
Geldenhuys, N

Objectives & Rationale
The objective of the study was to investigate the relationship between cardio-metabolic risk
phenotypes, serum iron parameters and high-sensitivity C-reactive protein (hs-CRP) as
inflammatory biomarker in relation to HFE genotype and alcohol intake in a South African
patient cohort. It is anticipated that insights gathered as a result of such investigation will
provide the basis for the development and subsequent validation of a pre-clinical screening tool
used to direct the need for HFE genotyping in the context of hepatic iron accumulation, with the
ultimate goal of limiting the need for extensive genetic testing as well as allowing liver biopsy to
be performed in a more goal-directed manner. Our previous studies have shown that guidelines
for safe drinking habits may in future be guided partly from the genetic background.

The study population included 500 South African patients referred for enrolment in a genomics
based chronic disease risk management program. Ferritin, hs-CRP and transferrin saturation
(TS) levels were evaluated in 273, 195 and 153 patients respectively. All study participants
were typed for the HFE C282Y (1800562 G>A) and H63D (rs1799945 C>G) mutations using
allele-specific TaqMan real-time polymerase chain reaction (RT-PCR) technology. A
questionnaire was used to document clinical data and lifestyle factors, including alcohol
consumption. Alcohol intake was differentiated into abstain, occasionally (1-2 units/week),
moderate (1-13 units/week), high (14-21units/week) and very high (≥22 units/week).

Key Results
BMI was positively correlated with hs-CRP (p<0.001) as well as ferritin (p=0.032) and
negatively correlated with TS levels (p<0.001) independent of HFE genotype. TS was further
positively correlated with ferritin (p=0.029) and negatively correlated with hs-CRP levels
(p=0.001). These associations were not affected by self-reported alcohol intake, despite the
significant alcohol-HFE gene interaction previously shown on the lipid profile after a 6-week
intervention study. See Appendix 1 for an example of a wellness screen report with
recommendations for a patient with genetic risk factors affected by alcohol intake.

The data generated in this study was incorporated into a pathology-supported genetic testing
algorithm incorporation . The mechanisms and modifying factors influencing the development of
iron-related diseases provide an excellent example of the genetic complexities inherent to
pathogenic processes. The current approach to the diagnosis and treatment of HH involves the
initial determination of the clinical and biochemical profile of the patient. When genetic testing is
requested for a patient by the referring healthcare practitioner, HFE gene mutation testing for
only C282Y, H63D and S65C is usually first performed. Based on the information provided in
the test report an optimal treatment is then devised, implemented and the response is
monitored according to the specific genetic and pathologic parameters provided by the testing
phase. A genetic counsellor can also be involved to facilitate prevention of HH in close family
members through early detection of a genetic predisposition that may become clinically relevant
in a high-risk environment if preventive measures are not implemented. High alcohol
consumption is considered an important environmental trigger of the deleterious genetic effects
associated with the above-mentioned HFE gene variants, as well as APOE 3937 T> C (allele
E4) and the MTHFR polymorphisms 677 C > T ( A222V) and 1298 A> C (E429A).

Grant, K A, Apffelstaedt, J P, Wright, C, Myburgh, E, Pienaar, R, De Klerk, M, Kotze, M J. MammaPrint pre-screen algorithm (MPA) reduces chemotherapy in patients with early-stage breast cancer, South African Medical Journal, Mnth Aug v. 103 (8) (p. 522-526)

Kotze, M P, Van Velden, D P. 2011. Waar staan ons nou met alkohol en gesondheid? WineLand, (p. 133-136)

Van Velden, D P, Kotze, M P, Blackhurst, D M, Kidd, M. 2011. Health claims on the benefits of moderate alcohol consumption in relation to genetic profiles, Journal of Wine Research, v. 22 (2) (p. 123-129)


Kotze, M J, Van Rensburg, S J. 2012. Pathology supported genetic testing and treatment of cardiovascular disease in middle age for the prevention of Alzheimer’s disease, Metabolic Brain Diseases, Mnth Sep v. 27 (p. 255-266)

Kotze, M J, Van Velden, D P, Botha, K, Badenhorst, C H, Avenant, H, Van Rensburg, S J, Cronje, F J. 2013. Pathology supported genetic testing directed at shared disease pathways for optimized health in later life, Personalized Medicine, v. 10 (5) (p. 521-526)

Kotze, M J, Marnewick, JL, Kidd, M, Fisher, L R, van Velden, D P. 2014. Assessment of the impact of hereditary factors on biochemical parameters of cardiovascular risk in relation to moderate alcohol consumption, Nutrition and Aging, v. 2 (2) (p. 189-195)

Lückhoff, H K, van Rensburg, S J, Botha, K, Kidd, M, Kotze, M J. 2014. The Pro-Inflammatory TNFA -308G>A (rs1800629) Polymorphism is associated with an earlier age at onset in patients with major depressive disorder, Journal of Psychiatry, v. 17 (3) (p. 1-6)

van Velden, D P, Kotze, M J. 2014. Integrative medicine – healthy aging, Nutrition and Aging, v. 2 (2,3) (p. 183-187)

Bezuidenhout, J, Apffelstaedt, J P, Hough, F S, Erasmus, R T, Schneider, J W. 2015. Genomic medicine and risk prediction across the disease spectrum, Critical Reviews in Clinical Laboratory Sciences, v. 52 (3)

Lückhoff, H K, Brand, T, van Velden, D P, Kidd, M, Fisher, L R, van Rensburg, S J, Kotze, M J. 2015. Clinical relevance of apolipoprotein E genotyping based on a family history of Alzheimer’s disease, Current Alzheimer Research, Mnth March v. 12 (3) (p. 210-217)

Kotze, M J. 2016. Application of advanced molecular technology in the diagnosis and application of genetic disorders in South Africa, Mnth May v. 106 (6) (p. 114-118)

Kotze MJ, Lückhoff HK, Peeters AV, Baatjes K, Schoeman M, van der Merwe L, Grant KA, Fisher LR, van der Merwe N, Pretorius J, van Velden DP, Myburgh EJ, Pienaar FM, van Rensburg SJ, Yako YY, September AV, Moremi KE, Cronje FJ, Tiffin N, Bouwens CSH, Bezuidenhout J, Apffelstaedt JP, Hough FS, Erasmus RT, Schneider JW. Genomic medicine and risk prediction across the disease spectrum. Crit Rev Clin Lab Sci 2015;19:1-15.

Luckhoff HK, Kidd M, van Rensburg SJ, van Velden DP, Kotze MJ. Apolipoprotein E genotyping and questionnaire-based assessment of lifestyle risk factors in dyslipidaemic patients with a family history of Alzheimer’s disease: test development for clinical application. Metab Brain Dis 2016; 31(1): 213-224.

Luckhoff HK, van Rensburg SJ, Kotze MJ, van Velden DP. Genetiese toets evalueer die effek van cholesterol en alkohol inname. Wynboer 2016.

Van Velden DP. Skink nog n doppie daar – of dalk nie? Universiteit Stellenbosch Geneeskunde & Gesondheidwetenskappe Nuusbrief 2015 (revised by MJ Kotze)

Van Rensburg, S J, Potocnik, F C V, Kotze, M J, Stein, D J. Abou-Saleh, M T (ed). 2010. Antemortem markers, IN: Principles and Practice of Geriatric Psychiatry. (p. 299-303) John Wiley, United Kingdom.



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