Introduction to Clinical Biochemistry

Mr. Arvind Kumar

Introduction 

  • Introduction to Clinical Biochemistry is a specialised branch of laboratory medicine that focuses on the measurement of biochemical substances (analytes) in various body fluids such as blood, urine, cerebrospinal fluid (CSF), and others.
  • It plays a pivotal role in understanding the biochemical basis of disease and in the diagnosis, prognosis, monitoring, and management of both acute and chronic illnesses.
  • It integrates basic biochemistry with clinical practice, allowing clinicians to interpret physiological data in terms of molecular function and pathology.

Historical Background

  • The roots of Clinical Biochemistry date back to the 19th century, with the advent of techniques for measuring urea, glucose, and creatinine.

  • The field advanced rapidly during the 20th century with the development of colorimetry, spectrophotometry, enzymology, and chromatography.

  • With automation, computerization, and immunoassays, clinical laboratories now provide rapid, accurate, and wide-ranging diagnostic services.

 

Objectives and Importance

  • Early disease detection: Many diseases manifest as biochemical changes before symptoms appear.

  • Assessment of disease severity and progression.

  • Monitoring therapeutic responses: E.g., blood glucose in diabetes.

  • Determining prognosis: E.g., cardiac enzymes after myocardial infarction.

  • Screening for genetic and metabolic disorders.

  • Research and drug development.

 

Body Fluids

Fluid Examples of Tests
Blood (serum/plasma) Glucose, electrolytes, liver/kidney function tests
Urine Albumin, ketones, proteins, electrolytes
CSF Glucose, proteins, and lactate
Synovial Fluid Uric acid, inflammatory markers
Pleural/Peritoneal Fluid Protein levels, LDH, and glucose

Common Biochemical Parameters in Clinical Practice

Carbohydrate Metabolism

  • Blood glucose

  • HbA1c (Glycated hemoglobin)

  • Glucose tolerance test (GTT)

Protein and Enzyme Markers

  • Serum albumin, globulins

  • Liver enzymes: AST, ALT, ALP, GGT

  • Cardiac markers: CK-MB, LDH, Troponins

  • Pancreatic enzymes: Amylase, lipase

Lipid Profile

  • Total cholesterol, HDL, LDL, triglycerides

  • Lipoprotein (a), apolipoproteins

Renal Function Tests (RFTs)

  • Blood urea nitrogen (BUN)

  • Serum creatinine

  • Uric acid

  • eGFR (estimated Glomerular Filtration Rate)

Electrolytes and Acid-Base Balance

  • Sodium, potassium, chloride, and bicarbonate

  • Blood pH, blood gases (pO₂, pCO₂)

Hormonal Assays

  • Thyroid: T3, T4, TSH

  • Adrenal: Cortisol, aldosterone

  • Pituitary: ACTH, GH, prolactin

  • Reproductive: Estrogen, progesterone, testosterone

Special Markers

  • Tumour markers: PSA, AFP, CEA, CA-125

  • Vitamins: B12, D, folate

  • Trace elements: Iron, zinc, copper, selenium

 

Techniques and Instrumentation

 

Technique Principle/Use
Spectrophotometry Measures the absorbance of light (e.g., glucose, bilirubin)
Electrophoresis Separation of proteins/lipoproteins
Chromatography Used in drug monitoring and toxicology
Immunoassays ELISA, RIA for hormone and protein assays
Ion-Selective Electrodes For electrolyte analysis
Autoanalyzers Automated analysis of multiple biochemical parameters

Clinical Application Examples

 

Disease Biochemical Tests
Diabetes mellitus Fasting glucose, HbA1c, urine ketones
Chronic kidney disease Urea, creatinine, electrolytes, eGFR
Liver diseases ALT, AST, ALP, bilirubin, PT/INR
Myocardial infarction Troponins, CK-MB, LDH
Thyroid dysfunction TSH, T3, T4

Quality Control and Assurance in Clinical Biochemistry

  • Internal Quality Control (IQC): Ensures accuracy and reliability of results on a daily basis.

  • External Quality Assessment (EQA): Compares results with other laboratories.

  • Standard Operating Procedures (SOPs): Maintain consistency in sample handling and analysis.

 

Recent Advances in Clinical Biochemistry

  • Point-of-care testing (POCT): Near-patient testing (e.g., glucometer).

  • Molecular diagnostics: PCR-based tests, gene expression profiling.

  • Proteomics and metabolomics: Identifying biomarkers for diseases.

  • Artificial Intelligence (AI) in result interpretation.