Hannelore Daniel

Type 2 diabetes metabolic footprint and biomarkers

Hannelore Daniel

Hannelore Daniel

SOME BASICS

glycerol

free fatty acids

free fatty acids

acylcarnitines

ketones

GLUCAGON

CATCHOLAMINES

Insulin

Insulin

GLUCAGON

CATCHOLAMINES

GLUCAGON

CATCHOLAMINES

free fatty acids

Catabolic state

Insulin

+

+

+

amino acids

amino acids

glucose

Hannelore Daniel

SOME BASICS

GLUCAGON

CATCHOLAMINES

Insulin

Insulin

GLUCAGON

CATCHOLAMINES

GLUCAGON

CATCHOLAMINES

Insulin

+

+

+

glycerol

free fatty acids

free fatty acids

acylcarnitines

ketones

free fatty acids

amino acids

amino acids

glucose

GLUCOSEAMINO ACIDSLIPIDS

Catabolic state

Hannelore Daniel

SOME BASICS

GLUCAGON

CATCHOLAMINES

Insulin

Insulin

GLUCAGON

CATCHOLAMINES

GLUCAGON

CATCHOLAMINES

Anabolic state

Insulin +

+

+

glycerol

free fatty acids

free fatty acids

acylcarnitines

ketones

free fatty acids

amino acids

amino acids

glucose

GLUCOSEAMINO ACIDSLIPIDS

Hannelore Daniel

SOME BASICS

GLUCAGON

CATCHOLAMINES

Insulin

Insulin

GLUCAGON

CATCHOLAMINES

GLUCAGON

CATCHOLAMINES

Anabolic state

Insulin +

+

+amino acids

glucose

amino acids

glucose

lipids

glucose

Hannelore Daniel

SOME BASICS

Hannelore Daniel

Hannelore Daniel

Obesity and the cause of the metabolic syndrome

Hannelore Daniel

Hannelore Daniel

Metabolomic (bio)markers of obesity, IR and type 2 diabetes

Hannelore Daniel

Insights gained in groups of monocygotic twins

Hannelore Daniel

monozygotic twinsdiscordant for obesity

Cell Metab. 2009 April; 9(4): 311–326.

Plasma Amino Acid Levels and Insulin Secretion in ObesityPhilip Felig, Errol Marliss and George F. Cahill, Jr.

N Engl J Med 1969; 281:811-816October 9, 1969

Metabolite markers of obesity

n=67n=74

Hannelore Daniel

The relationships between the mean expression of the BCAA catabolism pathway enzymes and markers of obesity in twins discordant for obesity

Pietiläinen KH, Naukkarinen J, Rissanen A, Saharinen J, et al. (2008) Global Transcript Profiles of Fat in Monozygotic Twins Discordant for BMI: Pathways behind Acquired Obesity . PLoS Med 5(3): e51. doi:10.1371/journal.pmed.0050051

18 monozygotic twinsdiscordant for obesity

Metabolite markers of obesity

Hannelore Daniel

Pietiläinen KH, Naukkarinen J, Rissanen A, Saharinen J, et al. (2008) Global Transcript Profiles of Fat in Monozygotic Twins Discordant for BMI: Pathways behind Acquired Obesity . PLoS Med 5(3): e51. doi:10.1371/journal.pmed.0050051

The relationships between the mean expression of the BCAA catabolism

pathway enzymes and markers of obesity in twins discordant for obesity

Metabolite markers of obesity

18 monozygotic twinsdiscordant for obesity

Hannelore Daniel

Samples derived from body mass index-(BMI) and age-matched

overweight to obese type 2 diabetic (n = 44) and non-diabetic (n = 12)

Gullah-speaking African-American women

Plasma metabolomic profiles reflective of glucose homeostasis in non-diabetic

and type 2 diabetic obese African-American women.

Urinary metabolic signatures of human adiposity. Elliott P, et al. Nicholson JK. Sci Transl Med. 2015 Apr 29;7(285):285

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discovery 1880 validation 444

NMR-based analysis in urine in reference in BMI

Hannelore Daniel

Biomarker discovery approaches in type 2 diabetes

Hannelore Daniel

An amino acid profile to predict diabetes?

Among 2.422 normoglycemic individuals followed for 12 years, 201 developed

diabetes

Hannelore Daniel

PLoS One. 2010 May 28;5(5):e10883.

Metabolite profiling in non-diabetic human volunteers with insulin resistance α-hydroxybutyrate is an early biomarker of insulin resistance and glucose intolerance in a nondiabetic population.

Hannelore Daniel

Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach

Diabetes. 2012 Oct 4. , Mol Syst Biol. 2012 Sep 25;8:615

from 866 to 238 with impaired glucose tolerance to 91 people with type 2 diabetes

Hannelore Daniel

Targeted High Performance Liquid Chromatography Tandem Mass Spectrometry-based Metabolomics differentiates metabolic syndrome from

obesity. Zhong F et al. Exp Biol Med (Maywood). 2017 Apr;242(7):773-780.

43 obese 26 obese/metS

Hannelore Daniel

A systems view of type 2 diabetes-associated metabolic perturbations in saliva, blood and urine at different timescales of glycaemic control.

Yousri NA, et al. Suhre K. Diabetologia. 2015 Aug;58(8):1855-67.

Selected gaussian graphical networks across biofluids

188 controls 181 type2 diabetics

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HUMAN GENETICS for identification of causes

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Manhattan plot of the association of genetic variants with the levels of branched-chain amino acids.

Genetic Predisposition to an Impaired Metabolism of the Branched-Chain Amino Acids and Risk of Type 2 Diabetes: A Mendelian Randomisation Analysis.

Lotta LA et. Al. Langenberg C. PLoS Med. 2016 Nov 29;13(11):e1002179.

meta-analysis of 1.992 incident type 2 diabetes and 4.319 non-cases

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Schematic representation of the branched-chain amino acid pathway and associations with type 2 diabetes. BCKD, branched-chain alphaketoacid dehydrogenase.

Genetic Predisposition to an Impaired Metabolism of the Branched-Chain Amino Acids and Risk of Type 2 Diabetes: A Mendelian Randomisation Analysis.

Lotta LA et. Al. Langenberg C. PLoS Med. 2016 Nov 29;13(11):e1002179.

meta-analysis of 1.992 incident type 2 diabetes and 4.319 non-cases

Hannelore Daniel

Genetic Predisposition to an Impaired Metabolism of the Branched-Chain Amino Acids and Risk of Type 2 Diabetes: A Mendelian Randomisation Analysis.

Lotta LA et. Al. Langenberg C. PLoS Med. 2016 Nov 29;13(11):e1002179.

meta-analysis of 1.992 incident type 2 diabetes and 4.319 non-cases

Hannelore Daniel

Heritability was estimated using multilevel mixed-effects linear regression adjusting for gestationalage, gender, weight and age.The highest heritability was for short-chainacylcarnitines (mainly C4 and C5). There is directevidence for a strong genetic contribution. To themetabolic profile at birth and that newbornscreening data can be utilized for studying thegenetic regulation of many clinically relevantmetabolites.

The heritability of metabolomic profiles in newborn twins

Heritability of analyzed metabolites and analyte ratios. The y-axis is the negative log10 of the P-value for additive genetic component and the heritabilityestimate is on the x-axis. Confidence intervals around the heritability point estimates are in light gray bars. IRT, TSH, 17-OHP and GALT are represented asdark gray squares, amino acids are represented as medium gray circles and acylcarnitines are represented as light gray triangles.

Heredity (Edinb). 2013 Mar; 110(3): 253–258.

after bariatric surgery

BC

CA

tra

nsa

min

ase

pro

tein

(arb

irar

y u

nit

s)

before bariatric surgery

Hannelore Daniel

Selective down-regulation of BCATm in human obesity

Am J Physiol Endocrinol Metab. 2007 December; 293(6): E1552–E1563.

Effects of bariatric surgery

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How good are marker-metabolites for diagnosis ?

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Diabetes. 2013 Feb; 62(2): 639–648.

from 866 to 238 with impaired glucose tolerance to 91 people with type 2 diabetes

Hannelore Daniel

Validation of a metabolite panel for early diagnosis of type 2 diabetes. Carter TC, et al. Metabolism. 2016 Sep;65(9):1399-408.

78 controls 61 type2 diabetics

Hannelore Daniel

Using animals to identify the origins of changes

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Metabolite profiling in plasma and tissues of ob/ob and db/db mice identifies novel markers of obesity and type 2 diabetes.

Giesbertz P, et al. Daniel H. Diabetologia. 2015;58(9):2133-43.

Hannelore Daniel

C0

C2

C5.OH

C3.0

X2.M.C3.0

C4.0

C5.1

C4.1.DC

C3.DC

C4.DC

C6.0

C3.DC.M

C5.DC

C5.1.DC

C5.M.DC

C7.DC

C8.0

C10.0

C12.0

C16.2

C14.0

C16.OH

C18.1.OH

C16.1

C18.2

C16.0C18.1

C12.DC

C18.0

X2.M.C4.0

X3.M.C4.0

C5.0

C4.OH.a

C4.OH.b

X2.M.C3.OH iso.C15.0

C15.0

iso.C17.0

C17.0

iso.C13.0

C13.0

C7.0

C6.OH.a..7.30.

C6.OH.b..7.55.

C0

C3.1

C2

C5.OH

C3.0

X2.M.C3.0

C4.0

C5.1

C4.1.DC

C3.DC

C4.DC

C6.0

C3.DC.M

C5.DC

C5.M.DC

C7.DC

C8.0

C9.0

C14.2.OH

C10.0

C12.1

C14.2

C12.0

C14.1

C16.2

C14.0

C16.OH

C18.1.OH

C16.1

C18.2

C16.0

C18.1

C12.DC

C18.0

X2.M.C4.0

X3.M.C4.0

C5.0

C4.1

X2.M.C3.1C4.OH.a

C4.OH.b

X2.M.C3.OH

C6.DC

iso.C15.0

C15.0

iso.C17.0

C17.0

iso.C13.0

C13.0

iso.C11.0

C11.0

iso.C7.0

C7.0

C6.OH.a..7.30.

C6.OH.b..7.55.

X3.M.C4.1

X3.OH.3.M.C4.0

C0

C3.1

C2

C5.OH

C3.0

X2.M.C3.0

C4.0

C5.1

C3.DC

C4.DC

C6.0

C3.DC.M

C5.DC

C10.2

C8.0C10.1

C9.0

C14.2.OH

C10.0

C12.1

C16.2.OH

C14.2

C12.0

C14.1

C16.2

C14.0C16.OH

C18.1.OH

C16.1

C18.2

C16.0

C18.1

C12.DC

C18.0

X2.M.C4.0X3.M.C4.0

C5.0

C4.1

X2.M.C3.1

C4.OH.a

C4.OH.b

C6.DC

iso.C15.0C15.0

iso.C17.0

C17.0

iso.C13.0

C13.0

iso.C11.0

C11.0

iso.C7.0

C7.0

C6.OH.a..7.30.

C6.OH.b..7.55.

C0

C3.OH

C5.OH

X2.M.C3.0

C4.0

C5.1

C4.1.DCC3.DC

C4.DC

C6.0

C3.DC.M

C5.DC

C5.M.DC

C8.1

C7.DC

C10.2

C8.0

C9.0

C14.2.OH

C10.0

C12.1

C16.2.OH

C14.2

C12.0

C16.2

C14.0

C16.OH

C18.1.OH

C16.1

C18.2

C16.0

C18.1

C12.DCC18.0

X2.M.C4.0X3.M.C4.0

C5.0

C4.1

X2.M.C3.1

C4.OH.a

C4.OH.b

X2.M.C3.OH

C6.DC

iso.C15.0C15.0iso.C17.0

C17.0

iso.C13.0

C13.0

iso.C11.0

C11.0

iso.C7.0

C7.0

C6.OH.a..7.30.

C6.OH.b..7.55.

Plasma

Liver

Muscle

Kidney

Plasma

Liver

Muscle

Kidney

The correlation network shows the strongest correlations between individual

concentrations of acylcarnitines in plasma and tissues.

Hannelore Daniel

Branched-chain amino acids as biomarkers in diabetes. Giesbertz P, Daniel H. Curr Opin Clin Nutr Metab Care. 2016 Jan;19(1):48-54.

A working hypothesis for explaining the characteristic alterations of plasma metabolites in obesity, insulin-resistance and diabetes

Hannelore Daniel

Selective down-regulation of BCATm in rodent obesity models

Am J Physiol Endocrinol Metab. 2007 December; 293(6): E1552–E1563.

Hannelore Daniel

Identified plasma (bio)markers of insulin resistance & diabetes in humans

For insulin resistance and type 2 diabetes numerous studies have identified in plasma metabolomics approaches aminoacids and derivatives, novel ketone bodies and selected lipids (mainly lyso-PC´s) as biomarkers with predictive quality.

Leucine

Isoleucine

Valine

Glucose

α-keto-Isovalerate

Propionyl-carnitine

free fatty acids

Carnitine

acetyl-Carnitine

C4-Carnitine

LyoPC17:0

lysoPC18:0

lysoPC 18:1

lysoPC 18:2C5- Carnitine

PLASMA

PC aa 32:1

ether PC´s

Sphingomyelins

Tyr/Phe

Glycine

Methionine

Threonine

α-Aminobutyrate

2-OH-Butyrate

3-OH-Butyrate

2-AminoadipateLysine

3-methyl-2-oxovalerate

Mannose

Glyoxylate

Glucosamine

Hannelore Daniel

Metabolite-markers of obesity, insulin resistance and T2DM observed in human samples are mainly products of impaired amino

acid metabolism (in particular of branched chain amino acids, glycine, threonine and lysine) followed by entities from fatty and

carbohydrate metabolism.

The key determinant for most changes is likely the disbalance in insulin (sensitivity) to catabolic hormones signalling.

This „metabolic signature“ (footprint) however seems not o improve significantly diagnosis of insulin resistance or T2DM.

Take home message

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